Methods and devices for analysis of x-ray images

ABSTRACT

The present invention relates to methods and devices for analyzing x-ray images. In particular, devices, methods and algorithms are provided that allow for the accurate and reliable evaluation of bone structure from x-ray images.

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is a continuation-in-part of U.S. patentapplication Ser. No. 09/977,012, filed Oct. 11, 2001 which in turnclaims the benefit of U.S. Provisional Patent Application Serial No.60/240,157 filed Oct. 11, 2000, from which priority is claimed under 35U.S.C. §119(e)(1), and which applications are all incorporated herein byreference in their entireties.

TECHNICAL FIELD

[0002] The present invention is in the field of x-ray imaging andanalysis thereof. In particular, methods and compositions for theaccurate analysis of bone mineral density and/or bone structure based onx-rays are described.

BACKGROUND

[0003] X-rays and other x-ray image analysis are important diagnostictools, particularly for bone related conditions. Currently availabletechniques for the noninvasive assessment of the skeleton for thediagnosis of osteoporosis or the evaluation of an increased risk offracture include dual x-ray absorptiometry (DXA) (Eastell et al. (1998)New Engl J. Med 338:736-746); quantitative computed tomography (QCT)(Cann (1988) Radiology 166:509-522); peripheral DXA (pDXA) (Patel et al.(1999) J Clin Densitom 2:397-401); peripheral QCT (pQCT) (Gluer et. al.(1997) Semin Nucl Med 27:229-247); x-ray image absorptiometry (RA)(Gluer et. al. (1997) Semin Nucl Med 27:229-247); and quantitativeultrasound (QUS) (Njeh et al. “Quantitative Ultrasound: Assessment ofOsteoporosis and Bone Status” 1999, Martin-Dunitz, London England; U.S.Pat. No. 6,077,224, incorporated herein by reference in its entirety).(See, also, WO 9945845; WO 99/08597; and U.S. Pat. No. 6,246,745).

[0004] DXA of the spine and hip has established itself as the mostwidely used method of measuring BMD. Tothill, P. and D. W. Pye, (1992)Br J Radiol 65:807-813. The fundamental principle behind DXA is themeasurement of the transmission through the body of x-rays of 2different photon energy levels. Because of the dependence of theattenuation coefficient on the atomic number and photon energy,measurement of the transmission factors at 2 energy levels enables thearea densities (i.e., the mass per unit projected area) of 2 differenttypes of tissue to be inferred. In DXA scans, these are taken to be bonemineral (hydroxyapatite) and soft tissue, respectively. However, it iswidely recognized that the accuracy of DXA scans is limited by thevariable composition of soft tissue. Because of its higher hydrogencontent, the attenuation coefficient of fat is different from that oflean tissue. Differences in the soft tissue composition in the path ofthe x-ray beam through bone compared with the adjacent soft tissuereference area cause errors in the BMD measurements, according to theresults of several studies. Tothill, P. and D. W. Pye, (1992) Br JRadiol, 65:807-813; Svendsen, O. L., et al., (1995) J Bone Min Res10:868-873. Moreover, DXA systems are large and expensive, ranging inprice between $75,000 and $150,000.

[0005] Quantitative computed tomography (QCT) is usually applied tomeasure the trabecular bone in the vertebral bodies. Cann (1988)Radiology 166:509-522. QCT studies are generally performed using asingle kV setting (single-energy QCT), when the principal source oferror is the variable composition of the bone marrow. However, a dual-kVscan (dual-energy QCT) is also possible. This reduces the accuracyerrors but at the price of poorer precision and higher radiation dose.Like DXA, however, QCT are very expensive and the use of such equipmentis currently limited to few research centers.

[0006] Quantitative ultrasound (QUS) is a technique for measuring theperipheral skeleton. Njeh et al. (1997) Osteoporosis Int 7:7-22; Njeh etal. Quantitative Ultrasound: Assessment of Osteoporosis and Bone Status.1999, London, England: Martin Dunitz. There is a wide variety ofequipment available, with most devices using the heel as the measurementsite. A sonographic pulse passing through bone is strongly attenuated asthe signal is scattered and absorbed by trabeculae. Attenuationincreases linearly with frequency, and the slope of the relationship isreferred to as broadband ultrasonic attenuation (BUA; units: dB/MHz).BUA is reduced in patients with osteoporosis because there are fewertrabeculae in the calcaneus to attenuate the signal. In addition to BUA,most QUS systems also measure the speed of sound (SOS) in the heel bydividing the distance between the sonographic transducers by thepropagation time (units: m/s). SOS values are reduced in patients withosteoporosis because with the loss of mineralized bone, the elasticmodulus of the bone is decreased. There remain, however, severallimitations to QUS measurements. The success of QUS in predictingfracture risk in younger patients remains uncertain. Another difficultywith QUS measurements is that they are not readily encompassed withinthe WHO definitions of osteoporosis and osteopenia. Moreover, nointervention thresholds have been developed. Thus, measurements cannotbe used for therapeutic decision-making.

[0007] There are also several technical limitations to QUS. Many devicesuse a foot support that positions the patient's heel between fixedtransducers. Thus, the measurement site is not readily adapted todifferent sizes and shapes of the calcaneus, and the exact anatomic siteof the measurement varies from patient to patient. It is generallyagreed that the relatively poor precision of QUS measurements makes mostdevices unsuitable for monitoring patients' response to treatment. Gluer(1997) J Bone Min Res 12:1280-1288.

[0008] Radiographic absorptiometry (RA) is a technique that wasdeveloped many years ago for assessing bone density in the hand, but thetechnique has recently attracted renewed interest. Gluer et al. (1997)Semin Nucl Med 27:229-247. With this technique, BMD is measured in thephalanges. The principal disadvantage of RA of the hand is the relativelack of high turnover trabecular bone. For this reason, RA of the handhas limited sensitivity in detecting osteoporosis and is not very usefulfor monitoring therapy-induced changes.

[0009] Peripheral x-ray absorptiometry methods such as those describedabove are substantially cheaper than DXA and QCT with system pricesranging between $15,000 and $35,000. However, epidemiologic studies haveshown that the discriminatory ability of peripheral BMD measurements topredict spine and hip fractures is lower than when spine and hip BMDmeasurements are used. Cummings et al. (1993) Lancet 341:72-75; Marshallet al. (1996) Br Med J 312:1254-1259. The main reason for this is thelack of trabecular bone at the measurement sites used with thesetechniques. In addition, changes in forearm or hand BMD in response tohormone replacement therapy, bisphosphonates, and selective estrogenreceptor modulators are relatively small, making such measurements lesssuitable than measurements of principally trabecular bone for monitoringresponse to treatment. Faulkner (1998) J Clin Densitom 1:279-285;Hoskings et al. (1998) N Engl J Med 338:485-492. Although attempts toobtain information on bone mineral density from dental x-rays have beenattempted (See, e.g., Shrout et al. (2000) J. Periodonol. 71:335-340;Verhoeven et al. (1998) Clin Oral Implants Res 9(5):333-342), these havenot provided accurate and reliable results.

[0010] Furthermore, current methods and devices do not generally takeinto account bone structure analyses. See, e.g., Ruttimann et al. (1992)Oral Surg Oral Med Oral Pathol 74:98-110; Southard & Southard (1992)Oral Surg Oral Med Oral Pathol 73:751-9; White & Rudolph, (1999) OralSurg Oral Med Oral Pathol Oral Radiol Endod 88:628-35.

[0011] Thus, although a number of devices and methods exist forevaluating bone density, there are a number of limitations on suchdevices and methods. Consequently, the inventors have recognized theneed, among other things, to provide methods and compositions thatresult in the ability to obtain accurate bone mineral density and bonestructure information from x-ray images and data.

SUMMARY

[0012] The present invention meets these and other needs by providingcompositions and methods that allow for the analysis of bone mineraldensity and/or bone structure from x-ray images. The x-ray images canbe, for example, dental or hip radiographs. Also provided are x-rayassemblies comprising accurate calibration phantoms including, inparticular, calibration phantoms which act as references in order todetermine bone structure from an x-ray image.

[0013] In one aspect, the invention includes a method to derivequantitative information on bone structure and/or bone mineral densityfrom a x-ray image comprising (a) obtaining an x-ray image, wherein thex-ray image includes an external standard for determining bonestructure; and (b) analyzing the image obtained in step (a) to derivequantitative information on bone structure. The x-ray image (radiograph)can be, for example, a hip radiograph or a dental x-ray obtained ondental x-ray film with or without an external standard comprising acalibration phantom that projects free of the mandible or maxilla. Thecalibration phantom can comprise geometric patterns, for example, madeof plastic, metal or metal powder.

[0014] In certain embodiments, the image is obtained digitally, forexample using a selenium detector system or a silicon detector system ora computed radiography system. In other embodiments, the image can bedigitized for analysis.

[0015] In any of the methods described herein, the analysis can compriseusing one or more computer program (or units). Additionally, theanalysis can comprise identifying one or more regions of anatomicalinterest (ROI) in the image, either prior to, concurrently or afteranalyzing the image, e.g. for information on bone mineral density and/orbone structure. Bone structural or bone density information at aspecified distance from the ROI and/or areas of the image havingselected bone structural or bone density information can be identifiedmanually or, preferably, using a computer unit. The region of interestcan be, for example, in the mandible, maxilla or one or more teeth. Thebone density information can be, for example, areas of highest, lowestor median density. Bone structural information can be, for example,trabecular thickness; trabecular spacing; two-dimensional orthree-dimensional spaces between trabeculae; two-dimensional orthree-dimensional architecture of the trabecular network.

[0016] In other aspects, the invention includes a method to derivequantitative information on bone structure from an x-ray imagecomprising: (a) obtaining an x-ray image; and (b) analyzing the imageobtained in step (a) using one or more indices selected from the groupconsisting of Hough transform, skeleton operator, morphologicaloperators, mean pixel intensity, variance of pixel intensity, fourierspectral analysis, fractal dimension, morphological parameters andcombinations thereof, thereby deriving quantitative information on bonestructure. The various analyses can be performed concurrently or inseries, for example a skeleton operator can be performed before a Houghtransform. Further, when using two or more indices they can be weighteddifferently. Additionally, any of these methods can also includeanalyzing the image for bone mineral density information using any ofthe methods described herein.

[0017] In another aspect, any of the methods described herein canfurther comprise applying one or more correction factors to the dataobtained from the image. For example, correction factors can beprogrammed into a computer unit. The computer unit can be the same onethat performs the analysis of the image or can be a different unit. Incertain embodiments, the correction factors account for the variation insoft-tissue thickness in individual subjects.

[0018] In another aspect, any of the methods described herein canfurther comprise compressing soft tissue in the image to a selectedthickness while obtaining the x-ray image.

[0019] In any of the assemblies described herein, the calibrationphantom can be integrated into the assembly, for example integrated intothe hygienic cover, x-ray film (e.g., between one or two layers of thefilm) and/or holder. Alternatively, the calibration phantom can betemporarily attached to the assembly, for example by insertion into acompartment of the hygienic cover or by mechanical attachment to thex-ray film. In certain embodiments, the calibration phantom comprises aplurality of geometric patterns (e.g., circles, stars, squares,crescents, ovals, multiple-sided objects, irregularly shaped objects andcombinations thereof) that serve as a reference for bone structurecharacteristics (e.g., trabecular thickness; trabecular spacing;two-dimensional or three-dimensional spaces between trabecular;two-dimensional and/or three-dimensional architecture of the trabecularnetwork). The calibration phantom (or geometric patterns therein) can bemade, for example, of metal, plastic, metal powder or combinationsthereof. In any of the assemblies described herein, the film can beintegral to the hygienic cover.

[0020] In a still further aspect, the invention includes a method ofdiagnosing a bone condition (e.g., osteoporosis, risk of fracture)comprising analyzing an x-ray obtained by any of the methods describedherein.

[0021] In a still further aspect, the invention includes a method oftreating a bone condition, for example by diagnosing the condition asdescribed herein and selecting and administering one or more therapiesto the subject.

[0022] In another aspect, the invention includes a method to deriveinformation on bone structure from an image comprising: (a) obtaining animage from a subject; (b) analyzing the image obtained in step (a) toderive quantitative information on bone structure. In certainembodiments, the analysis comprises comparing the information on bonestructure obtained from the image to a database of bone structuremeasurements obtained from selected subjects. The image can be, forexample, an x-ray image or an electronic image. In certain embodiments,the image comprises an external standard. The selected subjects makingthe database can be, for example, normal subjects, subjects withosteoporosis or combinations thereof. Further, the database cancomprises demographic data and data on bone structure in the subjects,for example, wherein said subjects are age, sex and race-matched.

[0023] In certain embodiments, the bone structure information isselected from the group consisting of trabecular thickness; trabecularspacing; trabecular connectivity, two-dimensional or three-dimensionalspaces between trabecular; two-dimensional or three-dimensionalarchitecture of the trabecular network and/or combinations thereof.Further, any of the methods described herein may further include thestep of locating one or more regions of interest (ROI) in said x-rayimage, for example, an ROI that is positioned using a regularized activeshape algorithm or an ROI that is located automatically.

[0024] In certain aspects, step (b) comprises analyzing the imageobtained in step (a) using one or more indices selected from the groupconsisting of trabecular density, trabecular perimeter, star volume,trabecular bone pattern factor, trabecular thickness, trabecularorientation, orientation-specific trabecular assessment, trabecularconnectivity and combinations thereof. In certain embodiments, theindices include at least one of the indices trabecular density anddensity is a ratio of trabecular area to total area. In otherembodiments, at least one of the indices is orientation-specifictrabecular assessment as determined using Fourier analysis. In otherembodiments, at least one of the indices is trabecular thickness asdetermined by Euclidean distance transformation. In other embodiments,at least one of the indices is trabecular orientation as determinedusing 2D fast Fourier Transform (FFT). In other embodiments, at leastone of the indices is trabecular connectivity as determined using nodecount. Further, two or more indices may be analyzed.

[0025] In another aspect, the invention includes a method of diagnosinga bone condition in a subject comprising analyzing information from animage according to any of the methods described herein, wherein if saidanalysis indicates that the bone structure information obtained from thesubject differs from that of normal control subjects, a bone conditionis diagnosed. The bone condition may be, for example, osteoporosis.

[0026] In yet another aspect, the invention comprises a method oftreating a bone condition comprising (a) obtaining an image from asubject; (b) analyzing the image obtained in step (a) to derivequantitative information on bone structure; (c) diagnosing a bonecondition based on the analysis of step (b); and (d) selecting andadministering a suitable treatment to said subject based on saiddiagnosis. In certain embodiments, analysis of the information obtainedin step (b) is conducted by comparing said information with informationin a database of bone structure measurements obtained from selectedsubjects. The treatment may comprise, for example, administering one ormore antiresorptive agents; administering one or more anabolic agents;or combinations thereof.

[0027] In another aspect, the invention includes a method of determiningbone mineral density from an x-ray image, the method comprising thesteps of (a) determining density of one or more internal standards insaid image; (b) creating a weighted mean between the values obtained instep (a); (c) utilizing said weighted mean to determine bone mineraldensity of bone in said image. The internal reference can be, forexample, selected from the group consisting of air, fat, water, metaland combinations thereof.

[0028] In another aspect, the invention includes a method of determiningbone structure from an x-ray image comprising the steps of (a)identifying one or more internal standards on said x-ray image; (b)determining the density or structure of said standard; and (c) utilizingthe density, structure or combinations thereof of said standard todetermine bone structure of the x-ray image. The internal reference canbe, for example, a tooth, a portion of a tooth, cortical bone, air,subcutaneous fat, and muscle.

[0029] In another aspect, the invention includes a method of evaluatingbone disease in a subject, the method comprising the steps of: (a)obtaining an x-ray image from said subject, wherein said image includesone or more bones; (b) assessing bone mineral density in at least oneanatomic region of said image; (c) assessing bone structure in saidregion; and (d) combining said assessments of bone mineral density andbone structure to evaluate bone disease. The bone disease can be, forexample, the risk of bone fracture such as osteoporotic fracture. Theevaluation can include, for example, diagnosing bone disease, monitoringthe progression of bone disease (e.g., by evaluating bone disease atvarious discrete time points) and the like. In certain embodiments, themethods described herein further comprising selecting a therapy based onthe evaluation of bone disease and administering said therapy to saidsubject. In further embodiments, the methods described herein theevaluation comprises monitoring the progression of bone disease duringor after administration of the selected therapy. In still furtherembodiments, any of the methods described herein can further comprisethe step of assessing one or more macro-anatomical parameters in saidimage and combining said assessment of bone mineral density, bonestructure and macro-anatomical parameters to diagnose bone disease.

[0030] In yet another aspect, the invention includes a method oftreating bone disease in a subject, the method comprising the steps of:(a) obtaining an image (e.g., x-ray or electronic image) from saidsubject, wherein said image includes one or more bones; (b) assessingbone mineral density in at least one anatomic region of said image; (c)assessing bone structure in said region; (d) combining said assessmentsof bone mineral density and bone structure to evaluate bone disease; (e)selecting a therapy based on the evaluation of bone disease; and (f)administering said therapy to said subject. In certain embodiments,steps (a) to (d) are performed two or more times. In other embodiments,steps (a) to (e) are performed two or more times.

[0031] In another aspect, the invention includes a method for evaluatingbone disease in a subject, the method comprising the steps of: (a)obtaining an image (e.g., x-ray or electronic image) of said subjectwherein said image includes one or more bones; (b) assessing bonestructure of said bone in said image; (c) assessing one or moremacro-anatomical parameters in said image; and (d) combining theassessments bone structure and macro-anatomical parameter assessment toevaluate bone disease. The bone disease can be, for example, the risk ofbone fracture such as osteoporotic fracture. The evaluation cancomprise, for example, diagnosing bone disease and/or monitoring theprogression of bone disease over two or more discrete time points (e.g.,by repeating steps (a) to (d) at two or more time points). The methodscan further comprise selecting a therapy based on the evaluation of bonedisease and administering said therapy to said subject. Further, theevaluation may comprise monitoring the progression of bone diseaseduring or after administration of said selected therapy.

[0032] These and other embodiments of the subject invention will readilyoccur to those of skill in the art in light of the disclosure herein.

BRIEF DESCRIPTION OF THE FIGURES

[0033]FIG. 1 shows an example of a dental x-ray. A calibration phantom110 is seen. Regions of interest 120 have been placed for measurement ofbone mineral density or structure.

[0034]FIG. 2 shows another example of a dental x-ray. A calibrationphantom 110 is seen. Regions of interest 120 have been placed formeasurement of bone mineral density or structure.

[0035]FIG. 3 shows an example of an analysis report resulting from ameasurement of mandibular or maxillary bone mineral density. A subject(X) is more than one standard deviation below the mean of age-matchedcontrols (x-axis age, y-axis arbitrary units BMD).

[0036]FIG. 4 shows an example of a V-shaped calibration phantom 110mounted on a tooth 120. Gums are also shown 130.

[0037]FIG. 5 shows an example of a holder 115 for a calibration phantom110. The holder 115 is mounted on a tooth 120. Gums are also shown 130.

[0038]FIG. 6, panels B through E shows gray value profiles alongdifferent rows of pixels used for locating dental apices. From top tobottom, the characteristic peaks for the dental roots (shown in dentalx-ray panel A) gradually disappear.

[0039]FIG. 7 shows a Hough transform (panel A) of a test image (panelB). All collinear points from the same line are transformed intosinusoidal curves that intersect in a single point (circles).

[0040]FIG. 8 shows a Hough transform (panel A) of a skeletonizedtrabecular bone x-ray image (panel B). The white regions in panel Aindicate longer segments and predominant angles.

[0041]FIG. 9 shows the effect of varying size of structuring element E₂;calibration phantom image with lines of varying width (1, 3, 5, 7, 9,11, 13 pix) (top left); skeleton operation performed using E₂ with adiameter of 3 pix (top right), 7 pix (bottom left), and 11 pix (bottomright), respectively.

[0042]FIG. 10 shows the effect of varying size of structuring elementE₂; gray scale image of trabecular bone (top left, panel A); skeletonoperation performed using E₂ with a diameter of 3 pix (top right, panelB); 7 pix (bottom left, panel C) and 11 pix (bottom right, panel D),respectively.

[0043]FIG. 11 shows gray value surface plot of an anatomical region ofinterest from a dental x-ray (inset) used for fractal analysis.

[0044]FIG. 12 shows an example of a hygienic cover holder that includescompartments for a calibration phantom and a fluid-filled bolus back.

[0045]FIG. 13 shows an example of an anatomical region of interest(black dot), determined relative to the teeth or to theconvexity/concavity of the mandible.

[0046]FIG. 14 shows an example of three anatomical region of interests(black dots), determined relative to the teeth or to theconvexity/concavity of the mandible.

[0047]FIG. 15 is a side view of an exemplary system for minimizing tubeangulation as described herein. In the Figure, the system is shown as adental x-ray system. An extension tubing (200) is attached to aring-shaped Rinn holder (102). The outer diameter of the extensiontubing is slightly smaller than the inner diameter of the tube locatedin front of the dental x-ray system/dental x-ray tube. The extensiontubing can then be inserted into the metal tube thereby reducing tubeangulation and resultant errors in bone apparent density and bonestructural measurements.

DETAILED DESCRIPTION

[0048] Before describing the present invention in detail, it is to beunderstood that this invention is not limited to particular formulationsor process parameters as such may, of course, vary. It is also to beunderstood that the terminology used herein is for the purpose ofdescribing particular embodiments of the invention only, and is notintended to be limiting.

[0049] The practice of the present invention employs, unless otherwiseindicated, conventional methods of x-ray imaging and processing withinthe skill of the art. Such techniques are explained fully in theliterature. See, e.g., X-Ray Structure Determination: A Practical Guide,2nd Edition, editors Stout and Jensen, 1989, John Wiley & Sons,publisher; Body C T: A Practical Approach, editor Slone, 1999,McGraw-Hill publisher; The Essential Physics of Medical Imaging, editorsBushberg, Seibert, Leidholdt Jr & Boone, 2002, Lippincott, Williams &Wilkins; X-ray Diagnosis: A Physician's Approach, editor Lam, 1998Springer-Verlag, publisher; and Dental Radiology: Understanding theX-Ray Image, editor Laetitia Brocklebank 1997, Oxford University Presspublisher.

[0050] All publications, patents and patent applications cited herein,whether above or below, are hereby incorporated by reference in theirentirety.

[0051] It must be noted that, as used in this specification and theappended claims, the singular forms “a”, “an”, and “the” include pluralreferents unless the content clearly dictates otherwise. Thus, forexample, reference to “a calibration phantom” includes a one or moresuch phantoms.

[0052] Definitions

[0053] Unless defined otherwise, all technical and scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which the invention pertains. Although any methodsand materials similar or equivalent to those described herein can beused in the practice for testing of the present invention, the preferredmaterials and methods are described herein.

[0054] The term “subject” encompasses any warm-blooded animal,particularly including a member of the class Mammalia such as, withoutlimitation, humans and nonhuman primates such as chimpanzees and otherapes and monkey species; farm animals such as cattle, sheep, pigs, goatsand horses; domestic mammals such as dogs and cats; laboratory animalsincluding rodents such as mice, rats and guinea pigs, and the like. Theterm does not denote a particular age or sex and, thus, includes adultand newborn subjects, whether male or female.

[0055] “Osteoporosis” refers to a condition characterized by low bonemass and microarchitectural deterioration of bone tissue, with aconsequent increase of bone fragility and susceptibility to fracture.Osteoporosis presents commonly with vertebral fractures or hip fracturesdue to the decrease in bone mineral density and deterioration ofstructural properties and microarchitecture of bone.

[0056] A “subject” preferably refers to an animal, for example a mammalsuch as a human. As used herein the term “patient” refers to a humansubject.

[0057] “Computational unit” refers to any current or future software,chip or other device used for calculations, such as bone structure, nowdeveloped or developed in the future. The computational unit may bedesigned to control the x-ray assembly or detector (as well as otherparameters related to the x-ray detector). Other applications of thecomputational unit to the methods and devices described herein will berecognized by those skilled in the art. The computational unit may beused for any other application related to this technology that may befacilitated with use of computer software or hardware.

[0058] “Bone structure” refers to two-dimensional or three-dimensionalarrangement (e.g., architecture or microarchitecture) of bone tissue.Generally, bone tissue includes two types of bone—an outer layer ofcortical bone that is generally mostly solid with some canals or porestherein and an inner layer of trabecular (or cancellous) bone thatgenerally is sponge-like or honeycomb-like in structure. Structuralfeatures or cortical and trabecular bone include, but are not limitedto, trabecular thickness; trabecular spacing; two-dimensional orthree-dimensional spaces between trabeculae; two-dimensional orthree-dimensional architecture of the trabecular network, solid material(typically greater than 3000 μm), primary and/or secondary trabeculae(typcially 75 to 200 μm), primary and secondary osteons (typically 100to 300 μm, plexiform, interstitial bone, trabecular packets, lamellae(typically 1 to 20 μm), lacunae, cement Lines, canaliculi,collagen-mineral composite (typically 0.06 to 0.4 μm), cortical pores,trabecular connectivity, nodes and branch points, and the like. One ormore of these and other structural features may be measured in thepractice of the present invention. Preferably, measurements are thesub-millimeter range, more typically in the 10-500 μm range.Non-limiting examples of microarchitecture parameters include trabecularstructure thresholded binary image parameters such as trabecular area;total area; trabecular area/total area; trabecular perimeter area;trabecular distance transform; marrow distance transform; trabeculardistance transform regional maxima values (mean, min., max, std. Dev);marrow distance transform regional maxima values (mean, min., max, std.Dev); star volume (see, e.g., Ikuta et. al. (2000) JBMR 18:217-277;Vesterby (1990) Bone 11: 149-155; and Vesterby et al. (1989) Bone10:7-13); trabecular Bone Pattern Factor (Hahn et. al., (1992) Bone13:327-330); TBPf=(P1-P2)/(A1-A2 ) where P1 and A1 are the perimeterlength and trabecular bone area before dilation and P2 and A2corresponding values after a single pixel dilation as well as trabecularskeleton parameters such as connected skeleton count or Trees (T); nodecount (N); segment count (S); node-to-node segment count (NN);node-to-free-end segment count (NF); node-to-node segment length (NNL);node-to-free-end segment length (NFL); free-end-to-free-end segmentlength (FFL); node-to-node total struts length (NN.TSL) (see, e.g.,Legrand et. al., (2000) JMBR 15:13-19; free-end-to-free-ends totalstruts length(FF.TSL); total struts length (TSL); FF.TSL/TSL;NN.TSL/TSL; Loop count (Lo); Loop area; mean distance transform valuesfor each connected skeleton; mean distance transform values for eachsegment (Tb.Th); mean distance transform values for each node-to-nodesegment (Tb.Th.NN); mean distance transform values for eachnode-to-free-end segment (Tb.Th.NF); orientation (angle) of eachsegment; angle between segments; length-thickness ratios (NNL/Tb.Th.NN)and (NFL/Tb.Th.NF); and interconnectivity index (ICI) whereICI=(N*NN)/(T*(NF+1).

[0059] “Macro-anatomical parameter” refers to any parameter describingthe shape, size or thickness of bone and/or surrounding structure,typically parameters that are greater than 0.5 mm in size in at leastone dimension. Macro-anatomical parameters include, for example, in thehip joint thickness of the femoral shaft cortex, thickness of thefemoral neck cortex, hip axis length, CCD (caput-collum-diaphysis) angleand width of the trochanteric region.

[0060] General Overview

[0061] Methods and compositions useful in analyzing x-ray images aredescribed. In particular, the invention includes methods of obtainingand/or deriving information about bone mineral density and/or bonestructure from an x-ray image. Additionally, the present inventionrelates to the provision of accurate calibration phantoms for use indetermining bone structure and methods of using these calibrationphantoms. In particular, the present invention recognizes for the firsttime that errors arising from misplacement of interrogation sites indental or hip x-rays of bone density and/or bone structure can becorrected by positioning the x-ray tube, the detector and/or thecalibration reference with respect to an anatomical landmark (oranatomical region of interest).

[0062] Advantages of the present invention include, but are not limitedto, (i) providing accessible and reliable means for analyzing x-rays;(ii) providing non-invasive measurements of bone structure andarchitecture; (iii) providing methods of diagnosing bone conditions(e.g., osteoporosis, fracture risk); (iv) providing methods of treatingbone conditions; and (iv) providing these methods in cost-effectivemanner.

[0063] 1.0. Obtaining Data from X-Rays

[0064] An x-ray image can be acquired using well-known techniques fromany local site. For example, in certain aspects, 2D planar x-ray imagingtechniques are used. 2D planar x-ray imaging is a method that generatesan image by transmitting an x-ray beam through a body or structure ormaterial and by measuring the x-ray attenuation on the other side ofsaid body or said structure or said material. 2D planar x-ray imaging isdistinguishable from cross-sectional imaging techniques such as computedtomography or magnetic resonance imaging. If the x-ray image wascaptured using conventional x-ray film, the x-ray can be digitized usingany suitable scanning device. Digitized x-ray images can be transmittedover a networked system, e.g. the Internet, into a remote computer orserver. It will be readily apparent that x-ray images can also beacquired using digital acquisition techniques, e.g. usingphotostimulable phosphor detector systems or selenium or silicondetector systems, the x-ray image information is already available indigital format which can be easily transmitted over a network.

[0065] Any x-rays can be used including but not limited to digitalx-rays and conventional x-ray film (which can be digitized usingcommercially available flatbed scanners). In certain embodiments, thex-ray is of the hip region, for example performed using standard digitalx-ray equipment (Kodak DirectView DR 9000, Kodak, Rochester, N.Y.).Patients are typically positioned on an x-ray table in supine position,parallel to the long axis of the table, with their arms alongside theirbody. The subject's feet may be placed in neutral position with the toespointing up or in internal rotation or may be placed in a foot holdersuch that the foot in a neutral position (0° rotation) or in any desiredangle of rotation (e.g., internal or external) relative to neutral (see,also Example 8 below). Foot holders suitable for such purposes mayinclude, for example, a base plate extending from the foot, for example,from the mid to distal thigh to the heel. The base plate preferably sitson the x-ray table. The patients' foot is positioned so that theposterior aspect of the heel is located on top of the base plate. Themedial aspect of the foot is placed against a medial guide connectedrigidly to the base plate at a 90° angle by any suitable means (e.g.,straps, velcro, plastic, tape, etc.). A second, lateral guide attachedto the base plate at a 90° angle with a sliding mechanism can then bemoved toward the lateral aspect of the foot and be locked in position,for example when it touches the lateral aspect of the foot. The use of afoot holder can help improve the reproducibility of measurements of bonestructure parameters or macro-anatomical parameters.

[0066] Generally, the ray is centered onto the hip joint medial andsuperior to the greater trochanter. A calibration phantom, such as analuminum step wedge may also be included in the images to calibrate grayvalues before further image analysis.

[0067] In other embodiments, dental x-rays are preferred because of therelative ease and lack of expense in obtaining these images. Further,the mandible and maxilla are primarily composed of trabecular bone.Since the metabolic turnover of trabecular bone is approximately eighttimes greater than that of cortical bone, areas of predominantlytrabecular bone such as the vertebral body are preferred sites formeasuring bone mineral density. Lang et al. (1991) Radiol Clin North Am29:49-76. Thus, the fact that trabecular bone is clearly visible on thedental x-ray image, thus lending itself to quantitative analysis of bonemineral density and structure. Jeffcoat et al. (2000) Periodontol23:94-102; Southard et al. (2000) J Dent Res 79:964-969. Further, theearliest bone loss in osteoporosis patients occurs in areas oftrabecular bone. Multiple dental x-ray images are commonly made in mostAmericans throughout life. Indeed, there are approximately 750 millionU.S. dental visits annually and 150 million of these patients result inmore than 1 billion dental x-rays taken each year. Thus, the ability todiagnose osteoporosis on dental x-rays would be extremely valuable sinceit would create the opportunity for low-cost mass screening of thepopulation.

[0068] Preferably, x-ray imaging is performed using standard x-rayequipment, for instance standard dental x-ray equipment (e.g. GeneralElectric Medical Systems, Milwaukee, Wis.). X-rays of the incisor regionand canine region are acquired using a standard x-ray imaging techniquewith 80 kVp and automatic exposure using a phototimer or using a manualtechnique with 10 mA tube current. X-ray images are acquired, forexample, on Kodak Ultraspeed film (Kodak, Rochester, N.Y.). X-ray imagesmay be digitized using a commercial flatbed scanner with transparencyoption (Acer ScanPremio ST).

[0069] 1.1. Calibration Phantoms

[0070] It is highly preferred that the x-ray images include accuratereference markers, for example calibration phantoms for assessing bonemineral density and/or bone structure of any given x-ray image.Calibration references (also known as calibration phantoms) for use inimaging technologies have been described. See, e.g., U.S. Pat. Nos.5,493,601 and 5,235,628. 5,335,260 discloses a calibration phantomrepresentative of human tissue containing variable concentrations ofcalcium that serves as reference for quantifying calcium, bone mass andbone mineral density in x-ray and CT imaging systems. However, currentlyavailable calibration phantoms are not always accurate. Because bonemineral density accounts for considerably less than 100% of fracturerisk in osteoporosis (Ouyang et al. (1997) Calif Tissue Int, 60:139-147)some of the methods and devices described herein are designed to assessnot only bone mineral density but also bone structure. By assessing boththese parameters, more accurate testing and screening can be providedfor conditions such as osteoporosis.

[0071] Thus, in certain aspects, the current invention provides formethods and devices that allow accurate quantitative assessment ofinformation contained in an x-ray such as density of an anatomicstructure and/or morphology of an anatomic structure. Any suitablecalibration phantom can be used, for example, one that comprisesaluminum or other radio-opaque materials. U.S. Pat. No. 5,335,260describes other calibration phantoms suitable for use in assessing bonemineral density in x-ray images. Examples of other suitable calibrationreference materials can be fluid or fluid-like materials, for example,one or more chambers filled with varying concentrations of calciumchloride or the like.

[0072] Numerous calibration phantoms (or reference calibrations) can beused in the practice of the present invention. Typically, the systemused to monitor bone mineral density and/or bone structure in a targetorganism comprises an x-ray (e.g., a dental or hip radiograph), whichprovides information on the subject; an assembly including a calibrationphantom, which acts as a reference for the data in the dental x-ray; andat least one data processing system, which evaluates and processes thedata from the dental x-ray image and/or from the calibration phantomassembly.

[0073] It will be readily apparent that a calibration phantom cancontain a single, known density or structure reference. Furthermore, agradient in x-ray density can be achieved by varying the thickness orthe geometry of the calibration phantom along the path of the x-raybeam, for example, by using a V-shape of the calibration phantom ofvarying thickness (FIG. 4). The calibration phantom can also includeangles. For example, the calibration phantom can be “T”-shaped or“L”-shaped thereby including one or more 90 degree angles.

[0074] The calibration phantom can contain several different areas ofdifferent radio-opacity. For example, the calibration phantom can have astep-like design, whereby changes in local thickness of the wedge resultin differences in radio-opacity. Stepwedges using material of varyingthickness are frequently used in radiology for quality control testingof x-ray beam properties. By varying the thickness of the steps, theintensity and spectral content of the x-ray beam in the projection imagecan be varied. Stepwedges are commonly made of aluminum, copper andother convenient and homogeneous materials of known x-ray attenuationproperties. Stepwedge-like phantoms can also contain calcium phosphatepowder or calcium phosphate powder in molten paraffin.

[0075] Alternatively, continuous wedges may be used or the calibrationreference may be designed such that the change in radio-opacity is fromperiphery to center (for example in a round, ellipsoid, rectangular,triangular of other shaped structure). As noted above, the calibrationreference can also be constructed as plurality of separate chambers, forexample fluid filled chambers, each including a specific concentrationof a reference fluid (e.g., calcium chloride). In addition to one ormore fluids, a calibration phantom can also contain metal powder, e.g.aluminum or steel powder, embedded within it (for example, embedded in aplastic).

[0076] In certain embodiments, the calibration phantom is specificallydesigned to serve as a reference for bone structure (e.g., trabecularspacing, thickness and the like). For example, the calibration wedge cancontain one or more geometric patterns with known dimensions, e.g. agrid whereby the spacing of a grid, thickness of individual gridelements, etc. are known. This known geometric pattern of radio-opaqueelements in the calibration phantom can be used to improve the accuracyof measurements of trabecular bone structure in an x-ray. Suchmeasurements of trabecular bone structure can include, but are notlimited to, trabecular spacing, trabecular length and trabecularthickness. Such measurements of trabecular spacing, trabecular lengthand trabecular thickness can, for example, be performed in a dental orhip x-ray. These calibration phantoms can be made up of a variety ofmaterials include, plastics, metals and combinations thereof. Further,the reference components can be solid, powdered, fluid or combinationsthereof. Thus, the calibration wedge can also be used to improvemeasurements of bone structure.

[0077] Since the present invention contemplates analysis of dental x-rayimages for information on bone structure, bone mineral density or bothstructure and density, it will be apparent that calibration phantomswill be selected based on whether structure, density or both are beingmeasured. Thus, one or more calibration phantoms may be present.

[0078] Whatever the overall shape or composition of the calibrationphantom, when present, the at least one marker be positioned at a knowndensity and/or structure in the phantom. Furthermore, it is preferredthat at least one geometric shape or pattern is included in thecalibration phantom. Any shape can be used including, but not limitedto, squares, circles, ovals, rectangles, stars, crescents,multiple-sided objects (e.g., octagons), V- or U-shaped, inverted V- orU-shaped, irregular shapes or the like, so long as their position isknown to correlate with a particular density of the calibration phantom.In preferred embodiments, the calibration phantoms described herein areused in 2D planar x-ray imaging.

[0079] The calibration phantoms can be imaged before or after the x-rayimage is taken. Alternatively, the calibration phantom can be imaged atthe same time as the x-ray image. The calibration phantom can bephysically connected to an x-ray film and/or film holder. Such physicalconnection can be achieved using any suitable mechanical or otherattachment mechanism, including but not limited to adhesive, a chemicalbond, use of screws or nails, welding, a Velcro™ strap or Velcro™material and the like. Similarly, a calibration phantom can bephysically connected to a detector system or a storage plate for digitalx-ray imaging using one or more attachment mechanisms (e.g., amechanical connection device, a Velcro™ strap or other Velcro™ material,a chemical bond, use of screws or nails, welding and an adhesive). Theexternal standard and the film can be connected with use of a holdingdevice, for example using press fit for both film and external standard.

[0080] Additionally, the calibration phantom assembly can be attached toan anatomical structure, for example one or more teeth, mucus membranes,the mandible and/or maxilla. For instance, the calibration phantom canbe attached (e.g., via adhesive attachment means) to the epithelium ormucous membrane inside overlying the mandible or the maxilla.Alternatively, the calibration phantom can be placed on or adjacent to atooth, for example, a V- or U-shaped (in the case of the maxilla) or aninverted V- or U-shaped (in the case of the mandible) calibrationphantom can be used. The opening of the V or U will be in contact withthe free edge of at least one tooth or possibly several teeth (FIG. 4).

[0081] In preferred embodiments, when an x-ray of an anatomic structureor a non-living object is acquired a calibration phantom is included inthe field of view. Any suitable calibration phantom can be used, forexample, one that comprises aluminum or other radio-opaque materials.U.S. Pat. No. 5,335,260 describes other calibration phantoms suitablefor use in assessing bone mineral density in x-ray images. Examples ofother suitable calibration reference materials can be fluid orfluid-like materials, for example, one or more chambers filled withvarying concentrations of calcium chloride or the like. In a preferredembodiment, the material of the phantom is stainless steel (e.g., AISIgrade 316 comprising carbon (0.08%); manganese (2%); silicon (1%);phosphorus (0.045%); sulphur (0.03%); nickel (10-14%); chromium(16-18%); molybdenum (2-3%); plus iron to make up 100%). The relativepercentages of the components may be with respect to weight or volume.

[0082] It will be apparent that calibration phantoms suitable forattachment to an anatomical structure can have different shapesdepending on the shape of the anatomical structure (e.g., tooth orteeth) on which or adjacent to which it will be placed including, butnot limited to, U-shaped, V-shaped, curved, flat or combinationsthereof. For example, U-shaped (or inverted U-shaped) calibrationphantoms can be positioned on top of molars while V-shaped (or invertedV-shaped) calibration phantoms can be positioned on top of incisors.Further, it will be apparent that in certain instances (e.g., teeth onthe mandible), the calibration phantom can rest on top of the tooth justbased on its gravity or it can be attached to the tooth (e.g., usingadhesive). In the case of the teeth on the maxilla, the calibrationphantom will typically be attached to the tooth, for example with use ofan adhesive.

[0083] Any of these attachments may be permanent or temporary and thecalibration phantom can be integral (e.g., built-in) to the film, filmholder and/or detector system or can be attached or positionedpermanently or temporarily appropriately after the film and/or filmholder is produced. Thus, the calibration phantom can be designed forsingle-use (e.g., disposable) or for multiple uses with different x-rayimages. Thus, in certain embodiments, the calibration phantom isreusable and, additionally, can be sterilized between uses. Integrationof a calibration phantom can be achieved by including a material ofknown x-ray density between two of the physical layers of the x-rayfilm. Integration can also be achieved by including a material of knownx-ray density within one of the physical layers of the x-ray film.Additionally, the calibration phantom can be integrated into the filmcover. A calibration phantom or an external standard can also beintegrated into a detector system or a storage plate for digital x-rayimaging. For example, integration can be achieved by including amaterial of known x-ray density between two of the physical layers ofthe detector system or the storage plate. Integration can also beachieved by including a material of know x-ray density within one of thephysical layers of the detector system or the storage plate.

[0084] In certain embodiments, for example those embodiments in whichthe calibration phantom is temporarily attached to a component of thex-ray assembly system (e.g., x-ray film holder, x-ray film, detectorsystem or the like), cross-hairs, lines or other markers may be placedon the apparatus as indicators for positioning of the calibrationphantom. These indicators can help to ensure that the calibrationphantom is positioned such that it doesn't project on materials thatwill alter the apparent density in the resulting image.

[0085] Any of the calibration phantom-containing assemblies describedherein can be used in methods of analyzing and/or quantifying bonestructure (or bone mineral density) in an x-ray image. The methodsgenerally involve simultaneously imaging or scanning the calibrationphantom and another material (e.g., bone tissue from a subject) for thepurpose of quantifying the density of the imaged material (e.g., bonemass). In the case of dental radiographs, the calibration phantom, thex-ray tube or dental x-ray film is typically positioned in a manner toensure inclusion of the calibration phantom and a portion of themandible and/or maxilla on the dental x-ray image. Preferably, thecalibration phantom, the x-ray tube and the dental x-ray film arepositioned so that at least a portion of the section of the mandible ormaxilla included on the image will contain predominantly trabecular bonerather than cortical bone.

[0086] Thus, under the method of the present invention, the calibrationphantom is preferably imaged or scanned simultaneously with theindividual subject, although the invention allows for non-simultaneousscanning of the phantom and the subject. Methods of scanning and imagingstructures by x-ray imaging technique are well known. By placing thecalibration phantom in the x-ray beam with the subject, referencecalibration samples allow corrections and calibration of the absorptionproperties of bone. When the phantom is imaged or scanned simultaneouslywith each subject, the variation in x-ray beam energy and beam hardeningare corrected since the phantom and the subject both see the same x-raybeam spectrum. Each subject, having a different size, thickness,muscle-to-fat ratio, and bone content, attenuate the beam differentlyand thus change the effective x-ray beam spectrum. It is necessary thatthe bone-equivalent calibration phantom be present in the same beamspectrum as the subject's bone to allow accurate calibration.

[0087] X-ray imaging assemblies that are currently in use do not takeinto account the position of the calibration phantom in relation to thestructures being imaged. Thus, when included in known assemblies,calibration phantom(s) are often positioned such that they project onmaterials or structures (e.g., bone) that alter apparent density of thecalibration phantom in the resulting x-ray image. Clearly, thisalteration in apparent density will affect the accuracy of thecalibration phantom as a reference for determining bone mineral density.Therefore, it is an object of the invention to provide methods in whichthe calibration phantom projects free of materials or structures thatwill alter the apparent density of the reference. In the context ofdental x-rays, for instance, the methods described herein ensure thatthe calibration phantom projects free of bone (e.g., teeth, jaw) tissue.This can be accomplished in a variety of ways, for example, positioningthe calibration phantom in the x-ray film or in the x-ray film holdersuch that it will appear between the teeth in the dental x-ray.

[0088] The calibration phantom materials and methods of the presentinvention are preferably configured to be small enough and thin enoughto be placed inside the mouth, and the method of the present inventioncan be used to quantify bone mass using standard dental x-ray systems,for example by including temporary or permanent calibration phantoms indental x-ray film holders. Further, it is highly desirable that thecalibration phantom be positioned so that at least a portion doesn'tproject on structures or materials that will alter the apparent densityor structural characteristics of the calibration phantoms. It is alsopreferable to position calibration phantom at a defined distancerelative to at least one tooth or the mandible or the maxilla whereby asubstantial portion of the calibration phantom projects free of saidtooth, said mandible or said maxilla on the x-ray image. Any suitabledistance can be used, for example between about 1 mm and 5 cm or anyvalue therebetween.

[0089] A cross-calibration phantom can be used to optimize systemperformance, e.g. x-ray tube settings or film processor settings, or toimprove the comparability of different machines or systems, typicallylocated at different sites. For this purpose, a separate image may beobtained which does not include a patient or a body part. The imageincludes the primary calibration phantom used in patients, e.g. astep-wedge of known density, and the cross-calibration phantom. Theapparent density of the primary calibration phantom is then calibratedagainst the density of the cross-calibration phantom. The resultantcross-calibration of the primary phantom can help to improve theaccuracy of measurements of bone density, bone structure andmacro-anatomical parameters. It can also help improve the overallreproducibility of the measurements. In one embodiment of the invention,an x-ray technologist or a dental hygienist will perform across-calibration test once a day, typically early in the morning, priorto the first patient scans. The results of the cross-calibration or theentire cross-calibration study can be transmitted via a network to acentral computer. The central computer can then perform adjustmentsdesigned to maintain a high level of comparability between differentsystems.

[0090] 1.2. Inherent Reference Markers

[0091] In certain embodiments of the invention, information inherent inthe anatomic structure or the non-living object can be used to estimatethe density and/or structure of selected bone regions of interest withinthe anatomic structure or the non-living object. For example, since thex-ray density of muscle, fat, water (e.g., soft tissue), metal (e.g.,dental fillings) and air are typically known, the density of airsurrounding an anatomic structure or non-living object, the density ofsubcutaneous fat, and the density of muscle tissue can be used toestimate the density of a selected region of bone, for example withinthe distal radius. For instance, a weighted mean can be determinedbetween one or more of the internal standards (e.g., air, water, metal,and/or fat) and used as internal standards to determine bone density inthe same x-ray image. Similarly, the density of a tooth or a portion ofa tooth can be used to estimate the density of a selected region ofbone, e.g. an area in the mandible.

[0092] The information inherent in said anatomic structure can also becombined with information provided by the calibration phantom and thecombination can result in an improved accuracy of the calibrationphantom.

[0093] 1.3. Holders and Hygienic Covers

[0094] As noted above, in certain embodiments, a holder can be used toposition the calibration phantom. The holder can be U-shaped or V-shaped(FIG. 5) for ease in attachment to a tooth. The attachment can be, forexample, with an adhesive. The calibration phantom, in turn, can beattached to the holder. Similarly, the calibration phantom can beattached to holders comprising one or more molds of at least one or moreteeth. Additionally, the holder can be used to position both the filmand the calibration phantom relative to the osseous structure that willbe included in the x-ray image. In another embodiment, a holding devicethat can hold the x-ray film is integrated in the calibration phantom.This holding device can hold the film in place prior to taking thex-ray. The holding device can be spring-loaded or use other means suchas mechanical means of holding and stabilizing the x-ray film.

[0095] In certain embodiments, the holder may comprise a disposable orsterilizeable hygienic cover. See, e.g., WO 99/08598, the disclosure ofwhich is incorporated by reference herein in its entirety. Furthermore,the holder may comprise multiple components, for example, thecalibration phantom and a integrated or insertable bolus back that canserve to enhance the accuracy of the calibration phantom by accountingfor the effect of soft tissue that may project with the calibrationphantom and/or with the bone.

[0096] In certain embodiments, the calibration phantom can be configuredso that it stabilizes against the surrounding tissues on its own withoutthe use of an additional holder. The calibration phantom can beprotected with a hygienic cover.

[0097] The holder (e.g., hygienic cover) may be comprised of a rigidmaterial, a flexible material or combinations thereof. Furthermore, theholder may include one or more pockets/compartments adapted to receiveadditional components such as the calibration phantom, a bolus back orthe like. Additionally, one or more portions of the holder may beradiolucent.

[0098] 2.0. Analysis and Manipulation of Data

[0099] The data obtained from x-ray images taken as described above isthen preferably analyzed and manipulated. Thus, the systems andassemblies described herein can also include one or more computationalunits designed, for example, to analyze bone density or bone structuredata in the image; to identify an anatomical landmark in an anatomicalregion; to correct for soft tissue measurements; and/or to evaluate bonedensity and structure of the image. The computational unit can alsofurther comprise a database comprising, for example, referenceanatomical maps and the computational unit is further designed tocompare the anatomical map with the reference anatomical map. Thereference anatomical map may be historic (from the same or anotherpatient, generated as part of an interrogation protocol), or theoreticalor any other type of desired reference map.

[0100] Any x-ray image can be analyzed in order to obtain and manipulatedata. Thus, data points, derived data, and data attributes databaseaccording to the present invention may comprise the following: (1) thecollection of data points, said data points comprising informationobtained from an x-ray image, for example, bone mineral densityinformation or information on bone structure (architecture); and (2) theassociation of those data points with relevant data point attributes.The method may further comprise (3) determining derived data points fromone or more direct data points and (4) associating those data pointswith relevant data point attributes. The method may also comprise (5)collection of data points using a remote computer whereby said remotecomputer operates in a network environment.

[0101] In certain preferred embodiments, the information is obtainedfrom a dental x-ray image. As described herein, dental x-ray images canbe acquired at a local site using known techniques. If the x-ray imagewas captured using conventional x-ray film, the data points(information) of the x-ray image can be digitized using a scanningdevice. The digitized x-ray image information can then be transmittedover the network, e.g. the Internet, into a remote computer or server.If the x-ray image was acquired using digital acquisition techniques,e.g. using phosphorus plate systems or selenium or silicon detectorsystems, the x-ray image information is already available in digitalformat. In this case the image can be transmitted directly over thenetwork, e.g. the Internet. The information can also be compressedand/or encrypted prior to transmission. Transmission can also be byother methods such as fax, mail or the like.

[0102] 2.1. Data Points

[0103] Thus, the methods of and compositions described herein make useof collections of data sets of measurement values, for examplemeasurements of bone structure and/or bone mineral density from x-rayimages. Records may be formulated in spreadsheet-like format, forexample including data attributes such as date of x-ray, patient age,sex, weight, current medications, geographic location, etc. The databaseformulations may further comprise the calculation of derived orcalculated data points from one or more acquired data points. A varietyof derived data points may be useful in providing information aboutindividuals or groups during subsequent database manipulation, and aretherefore typically included during database formulation. Derived datapoints include, but are not limited to the following: (1) maximum bonemineral density, determined for a selected region of bone or in multiplesamples from the same or different subjects; (2) minimum bone mineraldensity, determined for a selected region of bone or in multiple samplesfrom the same or different subjects; (3) mean bone mineral density,determined for a selected region of bone or in multiple samples from thesame or different subjects; (4) the number of measurements that areabnormally high or low, determined by comparing a given measurement datapoint with a selected value; and the like. Other derived data pointsinclude, but are not limited to the following: (1) maximum value of aselected bone structure parameter, determined for a selected region ofbone or in multiple samples from the same or different subjects; (2)minimum value of a selected bone structure parameter, determined for aselected region of bone or in multiple samples from the same ordifferent subjects; (3) mean value of a selected bone structureparameter, determined for a selected region of bone or in multiplesamples from the same or different subjects; (4) the number of bonestructure measurements that are abnormally high or low, determined bycomparing a given measurement data point with a selected value; and thelike. Other derived data points will be apparent to persons of ordinaryskill in the art in light of the teachings of the present specification.The amount of available data and data derived from (or arrived atthrough analysis of) the original data provide provides an unprecedentedamount of information that is very relevant to management of bonerelated diseases such as osteoporosis. For example, by examiningsubjects over time, the efficacy of medications can be assessed.

[0104] Measurements and derived data points are collected andcalculated, respectively, and may be associated with one or more dataattributes to form a database. The amount of available data and dataderived from (or arrived at through analysis of) the original dataprovide provides an unprecedented amount of information that is veryrelevant to management of bone related diseases such as osteoporosis.For example, by examining subjects over time, the efficacy ofmedications can be assessed.

[0105] Data attributes can be automatically input with the x-ray imageand can include, for example, chronological information (e.g., DATE andTIME). Other such attributes may include, but are not limited to, thetype of x-ray imager used, scanning information, digitizing informationand the like. Alternatively, data attributes can be input by the subjectand/or operator, for example subject identifiers, i.e. characteristicsassociated with a particular subject. These identifiers include but arenot limited to the following: (1) a subject code (e.g., a numeric oralpha-numeric sequence); (2) demographic information such as race,gender and age; (3) physical characteristics such as weight, height andbody mass index (BMI); (4) selected aspects of the subject's medicalhistory (e.g., disease states or conditions, etc.); and (5)disease-associated characteristics such as the type of bone disorder, ifany; the type of medication used by the subject. In the practice of thepresent invention, each data point would typically be identified withthe particular subject, as well as the demographic, etc. characteristicof that subject.

[0106] Other data attributes will be apparent to persons of ordinaryskill in the art in light of the teachings of the present specification.

[0107] 2.2. Storage of Data Sets and Association of Data Points withRelevant Data Attributes

[0108] A number of formats exist for storing data sets andsimultaneously associating related attributes, including but not limitedto (1) tabular, (2) relational, and (3) dimensional. In general thedatabases comprise data points, a numeric value which correspond tophysical measurement (an “acquired” datum or data point) or to a singlenumeric result calculated or derived from one or more acquired datapoints that are obtained using the various methods disclosed herein. Thedatabases can include raw data or can also include additional relatedinformation, for example data tags also referred to as “attributes” of adata point. The databases can take a number of different forms or bestructured in a variety of ways.

[0109] The most familiar format is tabular, commonly referred to as aspreadsheet. A variety of spreadsheet programs are currently inexistence, and are typically employed in the practice of the presentinvention, including but not limited to Microsoft Excel spreadsheetsoftware and Corel Quattro spreadsheet software. In this format,association of data points with related attributes occurs by entering adata point and attributes related to that data point in a unique row atthe time the measurement occurs.

[0110] Further, rational, relational (Database Design for Mere Mortals,by Michael J. Hernandez, 1997, Addison-Wesley Pub. Co., publisher;Database Design for Smarties, by Robert J. Muller, 1999, Morgan KaufmannPublishers, publisher; Relational Database Design Clearly Explained, byJan L. Harrington, 1998, Morgan Kaufmann Publishers, publisher) anddimensional (Data-Parallel Computing, by V. B. Muchnick, et al., 1996,International Thomson Publishing, publisher; Understanding FourthDimensions, by David Graves, 1993, Computerized Pricing Systems,publisher) database systems and management may be employed as well.

[0111] Relational databases typically support a set of operationsdefined by relational algebra. Such databases typically include tablescomposed of columns and rows for the data included in the database. Eachtable of the database has a primary key, which can be any column or setof columns, the values for which uniquely identify the rows in a table.The tables in the database can also include a foreign key that is acolumn or set of columns, the values of which match the primary keyvalues of another table. Typically, relational databases also support aset of operations (e.g., select, join and combine) that form the basisof the relational algebra governing relations within the database.

[0112] Such relational databases can be implemented in various ways. Forinstance, in Sybase® (Sybase Systems, Emeryville, Calif.) databases, thetables can be physically segregated into different databases. WithOracle® (Oracle Inc., Redwood Shores, Calif.) databases, in contrast,the various tables are not physically separated, because there is oneinstance of work space with different ownership specified for differenttables. In some configurations, databases are all located in a singledatabase (e.g., a data warehouse) on a single computer. In otherinstances, various databases are split between different computers.

[0113] It should be understood, of course, that the databases are notlimited to the foregoing arrangements or structures. A variety of otherarrangements will be apparent to those of skill in the art.

[0114] 2.3. Data Manipulation

[0115] Data obtained from x-ray images as described herein can bemanipulated, for example, using a variety of statistical analyses, toproduce useful information. The databases of the present invention maybe generated, for example, from data collected for an individual or froma selected group of individuals over a defined period of time (e.g.,days, months or years), from derived data, and from data attributes.

[0116] For example, data may be aggregated, sorted, selected, sifted,clustered and segregated by means of the attributes associated with thedata points. A number of data mining software programs exist which maybe used to perform the desired manipulations.

[0117] Relationships in various data can be directly queried and/or thedata analyzed by statistical methods to evaluate the informationobtained from manipulating the database.

[0118] For example, a distribution curve can be established for aselected data set, and the mean, median and mode calculated therefor.Further, data spread characteristics, e.g. variability, quartiles andstandard deviations can be calculated.

[0119] The nature of the relationship between any variables of interestcan be examined by calculating correlation coefficients. Useful methodsfor doing so include but are not limited to the following: PearsonProduct Moment Correlation and Spearman Rank Order Correlation.

[0120] Analysis of variance permits testing of differences among samplegroups to determine whether a selected variable has a discernible effecton the parameter being measured.

[0121] Non-parametric tests may be used as a means of testing whethervariations between empirical data and experimental expectancies areattributable merely to chance or to the variable or variables beingexamined. These include the Chi Square test, the Chi Square Goodness ofFit, the 2×2 Contingency Table, the Sign Test, and the Phi CorrelationCoefficient.

[0122] There are numerous tools and analyses available in standard datamining software that can be applied to the analysis of the databases ofthe present invention. Such tools and analyses include, but are notlimited to, cluster analysis, factor analysis, decision trees, neuralnetworks, rule induction, data driven modeling, and data visualization.Some of the more complex methods of data mining techniques are used todiscover relationships that are more empirical and data-driven, asopposed to theory-driven, relationships.

[0123] Exemplary data mining software that can be used in analysisand/or generation of the databases of the present invention includes,but is not limited to: Link Analysis (e.g., Associations analysis,Sequential Patterns, Sequential time patterns and Bayes Networks);Classification (e.g., Neural Networks Classification, BayesianClassification, k-nearest neighbors classification, linear discriminantanalysis, Memory based Reasoning, and Classification by Associations);Clustering (e.g., k-Means Clustering, demographic clustering, relationalanalysis, and Neural Networks Clustering); Statistical methods (e.g.,Means, Std dev, Frequencies, Linear Regression, non-linear regression,t-tests, F-test, Chi2 tests, Principal Component Analysis, and FactorAnalysis); Prediction (e.g., Neural Networks Prediction Models, RadialBased Functions predictions, Fuzzy logic predictions, Times SeriesAnalysis, and Memory based Reasoning); Operating Systems; and Others(e.g., Parallel Scalability, Simple Query Language functions, and C++objects generated for applications). Companies that provide suchsoftware include, for example, the following: Adaptative Methods Groupat UTS (UTS City Campus, Sydney, NSW 2000), CSI®, Inc., (ComputerScience Innovations, Inc. Melbourne, Fla.), IBM® (International BusinessMachines Corporation, Armonk, N.Y.), Oracle® (Oracle Inc., RedwoodShores, Calif.) and SAS® (SAS Institute Inc., Cary, N.C.).

[0124] These methods and processes may be applied to the data obtainedusing the methods described herein, for example, databases comprising,x-ray image data sets, derived data, and data attributes.

[0125] In certain embodiments, data (e.g., bone structural informationor bone minderal density information) is obtained from normal controlsubjects using the methods described herein. These databases aretypically referred to as “reference databases” and can be used to aidanalysis of any given subject's x-ray image, for example, by comparingthe information obtained from the subject to the reference database.Generally, the information obtained from the normal control subjectswill be averaged or otherwise statistically manipulated to provide arange of “normal” measurements. Suitable statistical manipulationsand/or evaluations will be apparent to those of skill in the art in viewof the teachings herein. The comparison of the subject's x-rayinformation to the reference database can be used to determine if thesubject's bone information falls outside the normal range found in thereference database or is statistically significantly different from anormal control. Statistical significance can be readily determined bythose of skill in the art. The use of reference databases in theanalysis of x-ray images facilitates that diagnosis, treatment andmonitoring of bone conditions such as osteoporosis.

[0126] For a general discussion of statistical methods applied to dataanalysis, see Applied Statistics for Science and Industry, by A. Romano,1977, Allyn and Bacon, publisher.

[0127] The data is preferably stored and manipulated using one or morecomputer programs or computer systems. These systems will typically havedata storage capability (e.g., disk drives, tape storage, CD-ROMs,etc.). Further, the computer systems may be networked or may bestand-alone systems. If networked, the computer system would be able totransfer data to any device connected to the networked computer systemfor example a medical doctor or medical care facility using standarde-mail software, a central database using database query and updatesoftware (e.g., a data warehouse of data points, derived data, and dataattributes obtained from a large number of subjects). Alternatively, auser could access from a doctor's office or medical facility, using anycomputer system with Internet access, to review historical data that maybe useful for determining treatment.

[0128] If the networked computer system includes a World Wide Webapplication, the application includes the executable code required togenerate database language statements, for example, SQL statements. Suchexecutables typically include embedded SQL statements. The applicationfurther includes a configuration file that contains pointers andaddresses to the various software entities that are located on thedatabase server in addition to the different external and internaldatabases that are accessed in response to a user request. Theconfiguration file also directs requests for database server resourcesto the appropriate hardware, as may be necessary if the database serveris distributed over two or more different computers.

[0129] Usually each networked computer system includes a World Wide Webbrowser that provides a user interface to the networked database server.The networked computer system is able to construct search requests forretrieving information from a database via a Web browser. With access toa Web browser users can typically point and click to user interfaceelements such as buttons, pull down menus, and other graphical userinterface elements to prepare and submit a query that extracts therelevant information from the database. Requests formulated in thismanner are subsequently transmitted to the Web application that formatsthe requests to produce a query that can be used to extract the relevantinformation from the database.

[0130] When Web-based applications are utilized, the Web applicationaccesses data from a database by constructing a query in a databaselanguage such as Sybase or Oracle SQL which is then transferred to arelational database management system that in turn processes the queryto obtain the pertinent information from the database.

[0131] Accordingly, in one aspect the present invention describes amethod of providing data obtained from x-ray images on a network, forexample the Internet, and methods of using this connection to providereal-time and delayed data analysis. The central network can also allowaccess by the physician to a subject's data. Similarly, an alert couldbe sent to the physician if a subject's readings are out of apredetermined range, etc. The physician can then send advice back to thepatient via e-mail or a message on a web page interface. Further, accessto the entire database of data from all subjects may be useful to thefor statistical or research purposes. Appropriate network securityfeatures (e.g., for data transfer, inquiries, device updates, etc.) areof course employed.

[0132] Further, a remote computer can be used to analyze the x-ray thathas been transmitted over the network automatically. For example, x-raydensity information or structural information about an object can begenerated in this fashion. X-ray density information can, for example,be bone mineral density. If used in this fashion, the test can be usedto diagnose bone-related conditions such as osteoporosis.

[0133] 2.4. Graphical User Interface

[0134] In certain of the computer systems, an interface such as aninterface screen that includes a suite of functions is included toenable users to easily access the information they seek from the methodsand databases of the invention. Such interfaces usually include a mainmenu page from which a user can initiate a variety of different types ofanalyses. For example, the main menu page for the databases generallyinclude buttons for accessing certain types of information, including,but not limited to, project information, inter-project comparisons,times of day, events, dates, times, ranges of values, etc.

[0135] 2.5. Computer Program Products

[0136] A variety of computer program products can be utilized forconducting the various methods and analyses disclosed herein. Ingeneral, the computer program products comprise a computer-readablemedium and the code necessary to perform the methods set forth supra.The computer-readable medium on which the program instructions areencoded can be any of a variety of known medium types, including, butnot limited to, microprocessors, floppy disks, hard drives, ZIP drives,WORM drives, magnetic tape and optical medium such as CD-ROMs.

[0137] For example, once an x-ray image or data from that image istransmitted via a local or long-distance computer network and the dataon the x-ray received by a remote computer or a computer connected tothe remote network computer, an analysis of the morphology and densityof the bone can be performed, for example using suitable computerprograms. This analysis of the object's morphology can occur intwo-dimensions, although it is also possible in three-dimensions, inparticular when x-ray images have been acquired through the anatomicobject using multiple different x-ray transmission angles or x-rayplanes. For example, in imaging osseous structures, such analysis of thetransmitted x-ray image can be used to measure parameters that areindicative or suggestive of bone loss or metabolic bone disease. Suchparameters include all current and future parameters that can be used toevaluate osseous structures. For example, such parameters include, butare not limited to, trabecular spacing, trabecular thickness, trabecularconnectivity and intertrabecular space.

[0138] Information on the morphology or 2D or 3D structure of ananatomic object can be derived more accurately, when x-ray imageacquisition parameters such as spatial resolution are known. Otherparameters such as the degree of cone beam distortion can also behelpful in this setting.

[0139] As noted above, an x-ray image can be transmitted from a localsite into a remote server and the remote server can perform an automatedanalysis of the x-ray. Further, the remote server or a computerconnected to the remote server can then generate a diagnostic report.Thus, in certain embodiments, a computer program (e.g., on the remoteserver or on a computer connected to the remote server) can generatecharges for the diagnostic report. The remote server can then transmitthe diagnostic report to a physician, typically the physician whoordered the test or who manages the patient. The diagnostic report canalso be transmitted to third parties, e.g. health insurance companies.Such transmission of the diagnostic report can occur electronically(e.g. via e-mail), via mail, fax or other means of communication. All orsome of the transmitted information (e.g., patient identifyinginformation) can be encrypted to preserve confidentiality of medicalrecords.

[0140] Thus, one exemplary system is described herein for analyzing bonemorphology or structure in a subject system via a dental x-ray thatincludes at least a portion of the mandible and/or maxilla of a subject,followed by evaluation or the x-ray image. Dental x-rays are obtained inany conventional method. The x-ray produces an image that can beinterpreted (for example, employing a selected algorithm and/or computerprogram) by an associated system controller to provide a bone mineraldensity or bone structure evaluation for display.

[0141] In a further aspect of the present invention, the monitoringsystem can comprise two or more components, in which a first componentcomprises an x-ray image and calibration phantom that are used toextract and detect bone-related data on the subject, and a secondcomponent that receives the data from the first component, conducts dataprocessing on the data and then displays the processed data.Microprocessor functions can be found in one or both components. Thesecond component of the monitoring system can assume many forms

[0142] 3.0.0.0 Correction Factors

[0143] Although the presence of calibration phantoms greatly aids inincreasing the accuracy of data obtained from dental x-rays, the presentinventors also recognize that, in certain instances, there may be a needto apply one or more correction factors to further enhance accuracy ofthe data obtained from any given x-ray image. Such correction factorswill take into account one or more of a wide variety of influences(e.g.,. soft tissue thickness, region from which the data is extractedand the like) that can alter apparent density or structure informationon the x-ray image.

[0144] In this regard, one or more reference databases can be used forcalibration and normalization purposes. For example, image normalizationor correction of soft-tissue attenuation can be performed using patientcharacteristic data such as patient weight, height and body mass index.In one example, a higher soft-tissue attenuation can be assumed in highweight and low height subjects; a lower soft-tissue attenuation will beassumed in low weight and high height subjects.

[0145] In another embodiment, a standard calibration curve is applied tox-ray images, whereby said calibration curve can be derived fromreference x-rays obtained with use of calibration phantoms. For example,100 patients can undergo dental x-rays with a calibration phantom and astandard calibration curve can be derived from these images.

[0146] 3.1.0.0. Anatomical Landmarks

[0147] In one embodiment, identification of anatomic landmarks of thestructure to be analyzed or identification of anatomical landmarksadjacent to the structure to be analyzed with subsequent positioning andcomputer analysis of the x-ray image relative to these anatomiclandmarks or with subsequent positioning and computer analysis ofanatomical region of interest (ROI) relative to these anatomiclandmarks. The present invention includes also positioning dental orother x-ray detectors, positioning the dental x-ray tube, and analyzingthe resulting images using landmarks based on either 1) texturalinformation, 2.) structural information, 3.) density information (e.g.density), or 4) 2 or 3 dimensional contour information 5) a combinationsthereof of the tissue or structure to be measured and of tissues orstructures adjacent to the measurement site. The invention also includesmethods and devices that are not necessarily based solely on anatomicallandmarks, but in some applications can be combined with anatomicallandmark embodiments. Preferably, many of the embodiments describedherein are designed for automated use with a minimum of operatorintervene and preferably remote or computer control of such devices.

[0148] In one embodiment, an alignment device may be used to ensureperpendicular or near perpendicular alignment of the dental x-ray tuberelative to the dental film, thereby decreasing geometric distortionresulting from tube angulation. For example, a dental film holder ispositioned relative to an anatomical landmark, e.g. the posterior wallof the mandible in the incisor region. A side-view of an exemplaryalignment system using a dental x-ray film holder is shown in FIG. 15.The system includes bite block (100), stainless steel rod (101), film(103), optional calibration phantom (104), Rinn holder (102) typicallyhaving a ring or donut shape, and extension tubing (200). The extensiontubing is designed to fit within the Rinn holder and may be temporarilyor permanently attached. The system can achieve high reproducibility ofthe film position relative to an anatomical landmark such as thealveolar ridge or the posterior wall of the mandible. The extensiontubing allows for alignment of the x-ray tube so that it is nearperpendicular to the Rinn instrument and, ultimately, the dental film.

[0149] Since manual alignment of the dental x-ray tube, namely the tube(e.g., metal) located in front of the dental x-ray tube for pointing andalignment purposes, is often not very accurate with alignment errors of3, 5 or even more degrees, a mechanical or electromagnetic device ispreferably used in order to achieve perpendicular or near perpendicularalignment between the metal tube anterior to the x-ray tube and the Rinnholder. For example, the metal tube can be physically attached to theRinn holder with use of one or more Velcro™ straps or it can be alignedusing optical aids such as levels, cross-hairs, light sources (points orareas), etc. Alternatively, such physical attachment can be achievedwith use of one or more magnets rigidly attached to the dental x-raysystem metal tube and the Rinn holder. In this embodiment, the magnetson the Rinn holder and the dental x-ray system metal tube will bealigned and brought into physical contact. In another embodiment, anextension tube is attached, for example with an adhesive, to the Rinnholder. The extension tubing can also be an integral part of the Rinnholder. The extension tubing can be designed so that its inner diameteris slightly greater than the outer diameter of the dental x-ray systemmetal tube. The dental x-ray system metal tube is then inserted into theextension tubing attached to the Rinn holder thereby greatly reducingalignment error of the x-ray tube relative to the x-ray film.Alternatively, the extension tubing can be designed so that its outerdiameter is slightly smaller than the inner diameter of the dental x-raysystem metal tube. The dental x-ray system metal tube is then advancedover the extension tubing attached to the Rinn holder thereby greatlyreducing alignment error of the x-ray tube relative to the x-ray film.One of skill in the art will easily recognize in view of the teachingsherein that many other attachment means can be used for properlyaligning the dental x-ray tube with the dental x-ray film. Combinationsof attachment mechanisms are also possible.

[0150] The anatomical landmark that is selected is part of an anatomicalregion. An anatomical region refers to a site on bone, tooth or otherdefinable biomass that can be identified by an anatomical feature(s) orlocation. An anatomical region can include the biomass underlying thesurface. Usually, such a region will be definable according to standardmedical reference methodology, such as that found in Williams et al.,Gray's Anatomy, 1980. The anatomical region can be selected from thegroup consisting of an edge of the mandible, an edge of the maxilla, anedge of a tooth, valleys or grooves in any of these structures orcombinations thereof. The dental x-ray image can be readily taken so asto include the anatomical site. Other anatomical regions include but arenot limited to the hip, the spine, the forearm, the foot, and the knee.

[0151] For example, the region of interest is placed between the dentalapices and the inferior mandibular cortex. The apices can be foundautomatically in the following way: for each row of pixels, the grayvalue profile is examined. While a profile that intersects bone anddental roots in an alternating fashion has several distinct peaks andvalleys, a profile that only covers trabecular bone shows irregularchanges in the gray values (FIG. 6). The dental apices are located inthe transitional region between these two patterns.

[0152] The measurement techniques to assess trabecular bone structureare preferably designed to work without user intervention. In order tofully automate the process of analyzing dental x-rays, it is necessaryto develop a technique to locate the regions of interest (ROIs) that areused for the calculation of the structural parameters of the trabecularbone. If the profile for a particular row of pixels contains distinctpeaks, their number, width and height can be determined. Next, the rowsbelow these lines can be evaluated until the peaks have disappeared.This line determines the boundary, 5 mm below which the ROI can beplaced in the center between the longitudinal axes of the roots, whichcan also be determined from the row profiles (FIG. 6). At a pixel sizeof 0.042 mm×0.042 mm, which corresponds to a resolution of 600 dpi, theROI has a size of 5.4 mm×5.4 mm (128×128 pixels). For other scanningresolutions, the pixel resolution of the ROI can be adjustedaccordingly.

[0153] In the case of an edentulous patient, bone mineral density can bemeasured in all ROIs that are located on a line that is, for example, 8mm inferior and parallel to the alveolar ridge. The ROIs can be movedfrom left to right on a pixel-by-pixel basis. Eventually, the ROI withthe lowest BMD can be chosen for further evaluation of the structuralbone parameters. This helps to avoid inclusion of regions on the x-raywhere bone mineral density may be overestimated due to projection of thecurved parts of the mandible near the canine teeth. Alternatively, theROI with the median BMD can be used. Other statistical parameters can beemployed for this purpose.

[0154] Thus, software or other computational unit can identify theselected anatomic landmark in an interrogated x-ray image and directanalysis of the image using various parameters and analytic functions.Further, such software or other computational analytical unit can beused to identify areas of particular density at a certain distance fromthe selected landmark. Similarly, manual or computer analysis can beused to identify areas of lowest, highest, median or average density (orstructural characteristics) in relation to the selected landmark.

[0155] Further, the same landmark may be compared at different times(intra-landmark comparison) or one or more landmarks may be compared(inter-landmark comparison). For instance, an intra-landmark comparisoncan be used during a single interrogation protocol that entails multipleinterrogations of the same region with reference to a particularanatomical landmark. Statistical analysis as described herein and knownin the art can be performed.

[0156] Thus, the invention provides for means of assessing bonestructure, i.e. the two-dimensional or three-dimensional architecturalorganization of the trabecular bone including, but not limited to,measurement of trabecular spacing, trabecular thickness, trabecularlength and trabecular connectivity. Other examples of measurements ofbone structure are provided in Table 1. These measurements can be usedalone or enhanced with use of calibration phantoms or external standardsthat can allow a correction or normalization of image intensity and thatcan in certain embodiments also allow a correction of geometricdistortions for example resulting from cone beam geometry of an x-raybeam.

[0157] As described herein, one or more measurements of bone structurecan be used to select a therapy, for example the use of anabolic orantiresorptive agent in the case of bone loss or deterioration. Incertain embodiments, measurements of bone structure are conducted overtime to longitudinally monitor a subject's bone health longitudinallyover time. Measurements can be performed at different time points T1,T2, . . . , Tn and changes in said bone structure parameters can beregistered and used to track a patient's bone health. In either singleor longitudinally measurements, a physician can be apprised of themeasurements and can include a predetermined cut-off value (e.g., when abone structure parameter measured in a patient is more than one or twostandard deviations different from a normal, healthy referencepopulation) and use this information to select a therapy.

[0158] The data obtained and analyzed as described herein can be used tomonitor a patient's response to therapy. For example, informationregarding bone structural information in a patient receiving an anabolicor antiresorptive drug and be evaluated at different time intervals T1,T2, . . . , Tn and changes in said bone structure parameters can be usedin order to assess therapeutic efficacy. A physician can use thisinformation to adjust the dose of a drug administered (e.g., fortreatment of osteoporosis) or to change the drug regimen.

[0159] Other techniques using x-ray information such as tomosynthesiscan also be used for measuring bone structure and for selecting saidtherapy or monitoring said therapy.

[0160] Bone structure can be measured using a number of differenttechnical approaches. These include but are not limited to the HoughTransform, analysis of density and size distribution of trabeculae,multidimensional classification schemes, mean pixel intensity, varianceof pixel intensity, Fourier spectral analysis, fractal dimension andmorphological parameters.

[0161] 3.1.1.0. Hough Transform

[0162] The Hough transform (See, e.g., Hough “Machine analysis of bubblechamber pictures” in International Conference on High EnergyAccelerators and Instrumentation. 1959. CERN) can be used to detectgeometric objects in binary images. As an entirely new approach toassessing bone structure, the invention includes the use of such methodsto analyze direction and length of trabecular structures in bone x-rayimages. For this purpose, the region of interest (ROI) can be blurredwith a Gaussian filter. The pixel values of the filtered ROI can then besubtracted from those in the original ROI, and the value 128 can beadded at each pixel location. This results in an image with a mean grayvalue of 128, which is also used as a threshold to yield a binary imagein which the trabeculae are represented by the white pixels.

[0163] After a skeletonization step, a Hough transform with the lineparameterization ρ=x cos θ+y sin θ can be applied to the binary image inorder to find straight line segments. Here ρ is the perpendiculardistance of the line from the origin and θ is the angle between thex-axis and the normal. Each point ({circumflex over (x)}, ŷ) in theoriginal image is transformed into a sinusoidal curve ρ={circumflex over(x)} cos θ+ŷ sin θ in the (ρ, θ) plane of the transformed image (seeFIG. 7)). Ideally, the curves from collinear points in the originalimage intersect in a single point in the transformed image. However, the(ρ, θ) plane can be divided into bins, where each bin counts the numberof transformed curves that pass through it. This number corresponds tothe number of collinear points on a line segment in the original image,and thus the length of this segment. Furthermore, the transformed imageprovides information on the predominant angles of the line segments inthe original image (see FIG. 8).

[0164] The average length and the variance of the line segments, whichare calculated for all bins with a count above a certain threshold, canbe used as structural parameters for the shape of the bone trabeculae.Average length as well as the variability of the length to decrease inpatients with osteoporosis. The threshold has the effect that onlysegments of a certain minimal length are included in the calculation.Choosing the threshold so that it provides the best discriminationbetween healthy and diseased individuals can be readily determined byone of skill in the art in view of the teachings herein.

[0165] The “center of mass” of the transformed image h, given as${{CM} = {( {\sum\limits_{({\rho,\theta})}{( {\rho,\theta} )^{T}*{H( {\rho,\theta} )}}} )/{\sum\limits_{({\rho,\theta})}{H( {\rho,\theta} )}}}},$

[0166] in which each bin is interpreted as an element with a massequivalent to its count, is a way to measure the predominant angles ofthe trabecular segments. The angle at cm is measured with respect to thealveolar rim to obtain a standardized value. More importantly, thevariance of the segment angles (again measured after thresholding thebin counts) provides information on the anisotropy of the trabecularstructure. Histomorphological studies of osteoporotic vertebrae haveshown that the variability of trabecular orientations decreases with thedisease.

[0167] 3.1.2.0. Analysis of Density and Size Distribution of Trabeculae

[0168] Morphological operations such as variations of dilation anderosion and combinations thereof can also be used to detect the size ofstructures in gray scale or binary images. For example, a skeletonoperator can be used to extract and quantify trabeculae of differentsizes and directions, which results in a measure of the sizedistribution of trabecular structures. This skeleton operator is basedon the work described in Kumasaka et al. (1997) Dentomaxillofac Rad26:161-168 and works as follows:

[0169] Let a two-dimensional structuring element e be a function overthe window −m≦i, j≦m (m>0) with E(i, j)ε{0, 1}. The dilation operatorsets a pixel value f(x, y) in a gray scale image f to the maximum ofthose values within the window of size m, for which e(i, j)=1:${\lbrack {f \oplus E} \rbrack ( {x,y} )} = {\max\limits_{{{- m} \leq i},{j \leq m}}\{ { {f( {{x + i},{y + j}} )} \middle| {E( {i,j} )}  = 1} \}}$

[0170] The erosion operator is defined accordingly, using the minimuminstead of the maximum:${\lbrack {f \otimes E} \rbrack ( {x,y} )} = {\max\limits_{{{- m} \leq i},{j \leq m}}\{ { {f( {{x + i},{y + j}} )} \middle| {E( {i,j} )}  = 1} \}}$

[0171] ‘Opening’ is the operation of maximum search after minimumsearch:

f _(E)=(f{circumflex over (x)}E)⊕E

[0172] Accordingly, the ‘closing’ operation is defined as the minimumsearch after maximum search:

f ^(E)=(f⊕E){circumflex over (x)}E

[0173] If a fixed structuring element E₁ is given as E₁(i, j)=1 for−1≦i, j≦1, the skeleton operation is then defined as

S _(Trabeculae)(f)=(f{circumflex over (x)}E ₂)−[(f⊕E ₂) _(E) _(1])  (1)

[0174] E₂ is another structuring element that is of circular shape andcan be varied in size, and therefore renders the skeleton operatorsensitive to the size of the structures in the image. The erosion offwith E₂ erases the structures that are smaller than E₂ and extractsthose trabeculae that are at least equal in size. Those structures thatare exactly equal in size is reduced to a width of one pixel. Theopening step with E₁ causes all structures that are one pixel wide todisappear (second term in (1)). After subtraction of this term from thefirst one, only those trabecular structures that exactly match the sizeof E₂ remain. Finally, the image is thresholded with a level of 1. Theeffect of this operator is illustrated in FIG. 9.

[0175]FIG. 10 demonstrates the use of the skeleton operator with thesame structural element diameters as in FIG. 9 on a gray scale region ofinterest from a dental x-ray containing trabecular bone. The number ofbright pixels in the binary images resulting from each skeletonoperation corresponds to the portion of trabeculae of the particularsize in the original image. If the percentage of the bright pixels withrespect to the total number of pixels in each skeletonized image isplotted against the diameter of E₂, the “center of mass” of the curve,i.e. the predominant structure size, can be used as an index todiscriminate between osteoporotic and healthy bone.

[0176] Furthermore, the skeleton operator is preferably optimized andextended to detect structures that are oriented only in a specificdirection. This can be achieved by adding erosion operations to theskeleton operator with structural elements in which, for example, onlythe diagonal pixels are set to 1.

[0177] This can be used to calculate an anisotropy index, similar to theone derived from the Hough transform. Both anisotropy indices are testedwith respect to their potential to distinguish healthy from osteoporoticbone.

[0178] In a similar manner the sizes of the marrow spaces can beexamined. The skeleton operator is then defined as

S _(Marrow)(f)=(f⊕E ₂)−[(f⊕E ₂) ^(_(E)) _(1])

[0179] 3.1.3.0. Multidimensional Classification Schemes

[0180] In certain embodiments, it is preferred to use multiple indicesto measure bone structure parameter. Thus, novel approaches thatintegrate one or more suitable indices can be employed. The indices canbe optimized and incorporated into a multi-dimensional classificationscheme, for example using a nearest neighbor classification. Cover etal. (1967) IEEE Trans Inform Theory 13(1):21-7. (See, Example 3).

[0181] Table 1 provides examples of different analyses andanatomical/physiological correlates of the parameters that can bemeasured. TABLE 1 Analysis Anatomical/Physiological Correlates Houghtransform length and direction of trabeculae; anisotropy Morphologicalthickness and direction of trabeculae; anisotropy; operators thicknessand length of marrow spaces Mean pixel intensity bone mineral densityVariance of pixel complexity of trabecular structure intensity Fourierspectral complexity of trabecular structure analysis Fractal dimensioncomplexity of trabecular structure Morphological length, size oftrabeculae; complexity of trabecular parameters structure; length, sizeof marrow spaces; complexity of marrow space

[0182] 3.1.3.1 Mean Pixel Intensity

[0183] Mean pixel intensity is a general parameter for the bone mineraldensity. The degree to which x-rays passing through bone tissue areabsorbed depends on the bone's mineral content. Bone with a highermineral density absorbs a larger portion of x-rays, and thereforeappears brighter on the x-ray image.

[0184] The mean pixel intensity {overscore (f(x, y))} in the ROI iscalibrated against an aluminum calibration wedge that is included in theimage. The log of the average pixel intensity for each thickness levelof the calibration wedge is plotted against the thickness, which allows{overscore (f(x, y))} to be converted into a standardized aluminumthickness equivalent, which is used as the value for this parameter. Theautomatic recognition of the different thickness levels of thecalibration wedge are made possible by different geometric patternsscribed into the wedge which are shown in the x-ray image and can belocalized automatically.

[0185] 3.1.3.2. Variance of Pixel Intensity

[0186] The variance of the pixel gray values in the roi, var f(x, y),describes the variability of the pixel intensities and can therefore bea measure of the degree of trabeculation. A loss of trabecular bone ispredicted to be reflected by a decreased var f(x, y). Southard &Southard (1992) Oral Surg Oral Med Oral Pathol 74:111-117.

[0187] 3.1.3.3. Fourier Spectral Analysis

[0188] The spatial frequency spectrum of a texture provides informationabout its coarseness. Fine textural structures and edges in an imagecorrespond to high frequencies in the frequency domain, while coarsetextures are represented by lower frequencies. Applied to x-ray imagesof trabecular bone, this means that a region with coarse or littletrabeculation should exhibit a Fourier spectral energy concentration atlow spatial frequencies, whereas a region of fine trabecular structureshould show a spectral energy concentration at high frequencies.

[0189] Typically, the 2-dimensional Fourier coefficients for theselected ROI. These 2-dimensional coefficients are used to determine a1-dimensional power spectrum F(u) by averaging all coefficients overcircles with radii that correspond to the discrete spatial frequenciesu. The mean transform coefficient absolute value {overscore (|F(u)|)}and the mean spatial first moment$M_{1} = \frac{\sum\limits_{u = 2}^{N}{{{F(u)}} \cdot u}}{N - 1}$

[0190] of the absolute coefficients are determined after exclusion ofthe first (“DC”) coefficient. M₁ provides a measure for whichfrequencies contribute most to the energy of the spectrum, similar tothe “center of mass” of a geometric object.

[0191] 3.1.3.4. Fractal Dimension

[0192] A different approach to analyze the texture in an image is byfractal analysis. Fractals are objects that exhibit certain statisticalself-similar or self-affine properties, so that a portion of the object,scaled to its original size, has for example the same surface area (3-d)or the same perimeter (2-d) as the original object. In the context offractal analysis, the gray values in a particular texture can beinterpreted as an altitude, and the resulting 3-dimensional surface isanalyzed (FIG. 11).

[0193] Fractal dimension (fd) is the rate at which the perimeter orsurface area of an object increases as the measurement scale is reduced.Russ “The Image Processing Handbook,” Third edition ed. 1999, BocaRaton: CRC press. It is a measure for the complexity of a boundary orsurface and corresponds to the intuitive notion of an object'sroughness. Without being bound by one theory, it is postulated thatosteoporotic trabecular bone, in which trabeculae become thinner andlose their continuity, and therefore complexity is increased, shouldhave a higher fractal dimension than healthy bone.

[0194] The results from the several ways in which FD can be measured arenot comparable. Thus, various methods can be tested to determine whichone (or combination) provides the best discrimination between normal andosteoporotic subjects.

[0195] The first method is applied in the frequency domain aftercalculation of the ROI's 2-D power spectrum using a fast Fouriertransform (FFT). From the 2-D Fourier coefficients the 1-D powerspectrum is produced as described above for the Fourier analysis. Whenthis 1-D power spectrum is plotted as the logarithm of the power versusthe logarithm of the frequency, it must have a negative slope ofmagnitude b with 1<b<3 according to fractal theory. The FD value is thencalculated as FD₁=3.5−b/2.

[0196] Another approach, the Minkowski method, measures the difference(summed over the ROI) between an upper and lower envelope fitted to thesurface as a function of the size of the neighborhood used. Peleg et al.(1984) Anal Mach Intell 6(4):518-523. If δ (δ=1, 2, 3, . . . ) is thedistance between the envelopes and the surface, then the upper envelopeu_(δ) and the lower envelope l_(δ) are given byu₀(i, j) = l₀(i, j) = f(i, j)${u_{\delta + 1}( {i,j} )} = {\max \{ {{{u_{\delta}( {i,j} )} + 1},{\max\limits_{{{{({m,n})} - {({i,j})}}} \leq 1}\{ {u_{\delta}( {m,n} )} \}}} \}}$${l_{\delta + 1}( {i,j} )} = {\min \{ {{{l_{\delta}( {i,j} )} - 1},{\min\limits_{{{{({m,n})} - {({i,j})}}} \leq 1}\{ {l_{\delta}( {m,n} )} \}}} \}}$

[0197] where f(i, j) is the gray value of pixel (i, j) in the ROI. Thelog of the area A(δ), plotted against log(δ), yields a line with anegative slope of magnitude b′. The fractal dimension is then given byFD₂=2−b′. The area is calculated as${A(\delta)} = {{\frac{v_{\delta} - v_{\delta - 1}}{2}\quad {with}\quad v_{\delta}} = {\sum\limits_{{({i,j})} \in {ROI}}{( {{u_{\delta}( {i,j} )} - {l_{\delta}( {i,j} )}} ).}}}$

[0198] 3.1.3.5. Morphological Parameters

[0199] While the previous features and parameters provide rather generalinformation on trabecular bone structure, the following examplesdescribe more detailed aspects.

[0200] The gray scale region of interest is first binarized. Asdescribed in White et al. (1999) Oral Surg Oral Med Oral Patholo OralRadiol Endod 88:628-635, this can be achieved in the following way: TheROI is blurred by means of a Gaussian filter. The blurred ROI is thensubtracted from the original ROI, and the value 128 is added at eachpixel location. This results in an image with a mean gray value of 128,which is also used as a threshold, resulting in an image, in whichtrabeculae are white and marrow space is black.

[0201] From this binary image, the total number of white pixelsrepresents the trabecular area, which is calculated as a percentage ofthe total ROI area. The number of pixels on the outer trabecular bordermeasures the peripheral length of the trabeculae. The same parameterscan be measured for the marrow space by counting the black pixels.

[0202] After skeletonization of the binary image, the total length ofthe trabeculae is determined by the total number white pixels.Furthermore, the counts of the terminal points and of the branch pointsare expressed as a proportion of trabecular length. An estimate of theaverage length of the trabeculae is calculated as the ratio of totaltrabecular length and the sum of terminal points and branch points.

[0203] 3.2.0.0. Soft Tissue

[0204] Variations in soft tissue thickness can be significant inanalyzing and evaluating bone density and bone structure in x-rays.Accordingly, the invention also includes methods and devices forcorrecting for soft tissue in assessment of bone structure or densetissue, particularly for diagnosing and/or predicting osteoporosis orother bone conditions.

[0205] In certain embodiments, the x-ray image is a dental x-ray imageand such correction methods involve (a) interrogating at least a portionof a subject's mandible and/or maxilla with an x-ray detector; (b)producing an x-ray image of the interrogated mandible and/or maxilla;(c) obtaining data from the x-ray image regarding bone density or bonestructure; (d) interrogating the surrounding soft tissue to determinesoft tissue thickness; and (e) correcting the data obtained from thex-ray image by correcting for soft tissue thickness. Such study groupsinclude: non-osteoporotic premenopausal, non-osteoporoticpostmenopausal, osteoporotic postmenopausal patients. It will beapparent, although exemplified with respect to dental x-rays, that manyof the methods described herein can be applied to other x-ray images,e.g. hip or spine x-ray images.

[0206] Soft tissue thickness measured in a subject can also be comparedto reference soft tissue thickness obtained from a control population(e.g. age-, sex-, race-, or weight-matched normal subjects). Referencesoft tissue thickness can be generated by measuring soft tissuethickness in healthy subjects with normal vascular, cardiac, hepatic, orrenal function and no other underlying medical condition. Reference softtissue thickness can be expressed as but are not limited to, mean andstandard deviation or standard error. Reference soft tissue thicknesscan be obtained independently for patients 15-20, 20-30, 30-40, 40-50,50-60, 60-70, 70-80, and 80 and more years of age and are preferablyobtained separately for men and women and for race (e.g. Asian, African,Caucasian, and Hispanic subjects). Additionally, reference soft tissuethickness can be obtained for different subject weights within each age,sex, and racial subgroup.

[0207] Individual patients can be compared to reference soft tissuethickness. If patient's soft tissue thickness is elevated, a correctionfactor can be applied. The amount/magnitude of correction factor isinfluenced by the magnitude of increase in soft tissue thickness thatcan be influenced by the magnitude of fat, fibrous, and muscle tissuecontribution. Clinical study groups can be evaluated to generatedatabases for further study or to generate more refined correctionfactors. Such study groups include: non-edematous non-osteoporoticpremenopausal, non-edematous non-osteoporotic postmenopausal,non-edematous osteoporotic postmenopausal; edematous non-osteoporoticpremenopausal, edematous non-osteoporotic postmenopausal, and edematousosteoporotic postmenopausal patients. In each study group the followingprocedures can be performed for comparison: dual x-ray absorptiometry(“DXA”) of the spine, hip, or calcaneus, along with SOS and BUAmeasurements or quantitative computed tomography (“QCT”). Thus,correction for soft tissue thickness can also improve the accuracy anddiscriminatory power in the analysis of x-rays and other x-rays. Suchmethods can also be used to identify population with an increased ordecreased risk of bone conditions such as osteoporosis.

[0208] 4.0. Applications

[0209] The measurements of bone mineral density or trabeculararchitecture, for example in the mandible or maxilla or in the hip or inthe spine, can be used to derive an assessment of bone health in anysubject. Additionally, the analysis and manipulation of data from x-raysallows for the assessment of bone health that in turn can be used toprescribe a suitable treatment regime. Efficacy of a treatment regimecan also be assessed using the methods and devices described herein (forexample, using measurements of bone mineral density or trabeculararchitecture in the mandible or the maxilla or the hip or the spinetaken at two separate time points T1 and T2 to detect any difference inbone mineral density or trabecular architecture).

[0210] In addition, the methods described herein permit, for example,fully automated assessment of the structural organization andarchitectural arrangement of trabecular bone on standard hip radiographsas well as improved tools for monitoring progression of osteoporosis andtherapeutic response. In certain embodiments, the methods involvebinarizing and skeletonizing trabecular bone using morphologicaloperators with detection of branch points and endpoints of the skeletonnetwork and classification into free-end segments and node-to-nodesegments. In other embodiments, the methods involve measuring trabeculardensity, trabecular perimeter, trabecular bone pattern factor, segmentcount, segment length, angle of segment orientation and ratio ofnode-to-node segments to free-end segments based on the binarized and/orskeletonized images. In still further embodiments, the methods involve(a) measuring trabecular thickness using a Euclidean distance transform(see, also Example 3); (b) assessing trabecular orientation using a 2DFast Fourier Transform; and/or (c) creating a bone structure index fordiagnosing osteoporosis or for predicting fracture risk combining atleast two or more of these structural parameters.

[0211] In certain embodiments, the radiograph is of a subject's hip.Furthermore, to help control the influence of radiographic positioningon the accuracy of bone structure measurements, the methods may includeone or more of the following: evaluating the angular dependence of bonestructure measurements in the hip, for example by comparinganteroposterior radiographs of the hip joint in healthy to osteoporoticpatients (subjects) with the femur radiographs in neutral position andin various degrees of internal and external rotation or by obtainingradiographs of the hip with different degrees of tube angulation. Bonestructure measurements can be compared between the different positionsto determine which bone structure parameters show the least dependenceon radiographic positioning and/or using a foot holder to fix thepatients' foot in neutral position in case pair wise coefficients ofvariation between the results for the 0° neutral position and a 15°internal or external rotation position exceed 10% for the majority ofthe structural parameters measured.

[0212] In other embodiments, methods of monitoring bone structure overtime (e.g., longitudinally) are also provided, for example to assessprogression of osteoporosis and/or response to therapy. In certainembodiments, the methods involve automated placement of regions ofinterest (ROI) in the hip joint, for example by creating and using ageneral model of the proximal femur that includes six defined regions ofinterest (ROI's).

[0213] The methods described herein, which allow, in part, for themeasurement of bone structure are useful in both the diagnosis andtreatment of osteoporosis. Ultimately, these techniques could helpscreen large numbers of women at risk for osteoporosis in a highlycost-effective and accurate manner using standard, widely availableradiographic equipment without the need for expensive dedicated capitalequipment. It is clear that a program of this type would be powerfullyenabling for therapeutic intervention with new anabolic oranti-resorptive drugs that are needed to prevent the expected pandemicof osteoporotic fractures.

[0214] 4.1. Kits

[0215] The invention also provides kits for obtaining information fromx-ray images, for example for obtaining information regarding bonestructure from an x-ray such as a dental x-ray. In certain embodiments,the kit comprises one or more computer (e.g., software) programs, forexample for receiving, analyzing and generating reports based on x-rayimages. In further embodiments, the kits can include calibrationphantoms, for example calibration phantoms integrated or attachable-to aholder, hygienic cover, x-ray film and/or x-ray film holders.

[0216] The invention also provides for therapeutic kits, for example fortreating osteoporosis or dental disease. In certain embodiments, thekits comprise a calibration phantom for use with one or more x-rayfilms, a computer software product, a database, a therapeutic drug and,optionally, instructions for use (e.g., instructions regardingpositioning the calibration phantom while taking the x-ray, using thesoftware to analyze the x-ray, dosages and the like. The therapeuticdrug can be, for example, anti-resorptive or anabolic.

[0217] 4.2. Diagnosis and Prediction

[0218] In yet another aspect, methods of diagnosing or predictingbone-related disorders (e.g., osteoporosis, Paget's Disease,osteogenesis imperfecta, bone cancers), periodontal disease or oralimplant failure in a subject are provided, for example using any of thekits, methods and/or devices described herein. It will be apparent thatthese methods are applicable to any bone-related disorder including, forexample, osteoporosis, bone cancer, and the like, as well as toperiodontal disease and implant failure.

[0219] Osteoporosis alone is a major public health threat for 25 millionpostmenopausal women and 7 million men. In 1995, national directexpenditures for osteoporosis and related fractures were $13 billion.Changing demographics, with the growth of the elderly population,steadily contribute to increasing numbers of osteoporotic fractures andan incipient and potentially economically unmanageable epidemic ofosteoporosis. Projections put the total cost of osteoporosis in theUnited States alone at more than 240 billion dollars per year in 40years.

[0220] Less than 20% of the patients know they have the disease and manyfewer receive physician directed specific therapy. A major impediment insuccessfully dealing with the impending osteoporosis epidemic is not alack of treatment modalities but the inability to identify persons atrisk and who require treatment. The limited access to osteoporosistesting is largely the result of the high cost of the currentlyavailable systems resulting in a small installed base limited tohospitals and specialty clinics.

[0221] The devices and methods described herein address these and otherissues by providing inexpensive and reliable bone structural analysisscreens and resulting diagnosis of bone condition and/or presence ofdisease. Indeed, while measurements of bone mineral density (BMD) aretechnically relatively easy to perform, low BMD accounts forconsiderably less than 100% of fracture risk although it is wellestablished that progressive disruption of trabecular structure andarchitecture contribute in a major way to fracture risk in olderindividuals.

[0222] Thus, in certain embodiments, the methods comprise using acomputer program to analyze bone mineral density or bone structure of ax-ray image (e.g., dental x-ray image) and comparing the value ormeasurement obtained from the image with a reference standard or curve,thereby determining if the subject has a bone-related condition such asosteoporosis or thereby determining a subject's fracture risk. The x-rayimage can also include a calibration phantom, for example a calibrationphantom as described herein.

[0223] In certain embodiments, measurements of bone structure can becombined or correlated with measurements of macro-anatomicalparameters(e.g., cortical thickness on a hip x-ray), for example usingstatistical or mathematical methods, to create an index for the severityof the disease. Subsequently, the index can be used for diagnosingosteoporosis or for predicting fracture risk combining at least two ormore of these bone structure or morphological parameters.

[0224] 4.3. Treatment

[0225] The methods and devices described herein can also be used todevelop an appropriate treatment regime for a subject in need thereof.Additionally, the invention allows for the ongoing analysis of theefficacy of a subject's treatment regime.

[0226] Although estrogen deficiency after menopause is one of the mostwell documented causes of osteoporosis that can be prevented by hormonereplacement therapy (HRT), HRT may also cause an increase (approximately35%) in the risk of breast cancer in long-term users. Lancet(1997)350:1047-1059. Consequently, much effort has been devoted todeveloping alternative treatments for osteoporosis. Among thosetreatments, bisphosphonates are becoming increasingly recognized as thetreatment of choice. Lin (1996) Bone 18:75-85; Liberman et al. (1995) NEngl J Med 333:1437-1443; Mortensen et al. (1998) J Clin EndocrinolMetab 83:396-402. Another new class of therapeutic agents recentlyintroduced is the selective estrogen receptor modulators (SERMs). Delmaset al. (1997) N Engl J Med 337:1641-1647; Lufkin et al. (1998) J BoneMin Res 13:1747-1754. Anabolic therapies such as parathyroid hormonehave also been suggested for treatment of osteoporosis. Roe et al.(1999) J Bone Miner Res 14(suppl 1):S137, Abst#1019; Lane et al. (1998)J Clin Invest 102:1627-33.

[0227] The combined results of these and other studies suggest thateffective treatments for osteoporosis can be developed once thecondition is diagnosed. For instance, using any of the methods, kits,and/or devices described herein, the presence of osteoporosis in asubject can be diagnosed and that subject provided with appropriatetherapy (e.g., one or more anti-resorptive agents and/or one or moreanabolic agents). Periodontal disease can be similarly diagnosed andtreatments ranging from oral hygiene practices to surgery can berecommended. Over time, the methods described herein can be used toassess the efficacy of the selected treatment and the treatment regimealtered as necessary. Thus, in certain embodiments, treatment of bonerelated disorders are provided.

[0228] 4.4. Decision Trees

[0229] Thus, diagnosing, predicting, developing treatment regimes,assessing treatment efficacy and the like can be readily accomplishedusing the methods described herein. In certain aspects, theseapplications will be accomplished using algorithms or decision trees(also known as logic trees or flow charts). One exemplary decision treeis provided in regard to predicting bone problems. It will be readilyapparent that such decision trees are equally applicable to otherapplications (e.g., designing treatment regimes, assessing treatmentefficacy, etc.).

[0230] One exemplary method for predicting bone problems (e.g.,osteoporoses, etc.), periodontal disease or oral implant failure employsa decision tree (also called classification tree) which utilizes ahierarchical evaluation of thresholds (see, for example, J. J. Oliver,et. al, in Proceedings of the 5th Australian Joint Conference onArtificial Intelligence, pages 361-367, A. Adams and L. Sterling,editors, World Scientific, Singapore, 1992; D. J. Hand, et al., PatternRecognition, 31(5):641-650, 1998; J. J. Oliver and D. J. Hand, Journalof Classification, 13:281-297, 1996; W. Buntine, Statistics andComputing, 2:63-73, 1992; L. Breiman, et al., “Classification andRegression Trees” Wadsworth, Belmont, Calif., 1984; C4.5: Programs forMachine Learning, J. Ross Quinlan, The Morgan Kaufmann Series in MachineLearning, Pat Langley, Series Editor, October 1992, ISBN 1-55860-238-0).Commercial software for structuring and execution of decision trees isavailable (e.g., CART (5), Salford Systems, San Diego, Calif.; C4.5 (6),RuleQuest Research Pty Ltd., St Ives NSW Australia) and may be used inthe methods of the present invention in view of the teachings of thepresent specification. A simple version of such a decision tree is tochoose a threshold bone structure or bone mineral density reading at aparticular anatomical landmark (e.g., edge of mandible or maxilla, theend of a tooth root, etc.). If a value is equal to or below thethreshold bone data value, then more of the image is evaluated. If moreof the image is below the threshold value, then a bone problem,periodontal disease or implant failure is predicted.

[0231] For example, a first level decision is made by the algorithmbased on the most recent x-ray images obtained and analyzed as describedherein is compared to initial thresholds that may indicate an impendingor current bone- or periodontal-related event. For example, thealgorithm may compare the current bone structure measurements (time=n)or a predicted bone structure measurement (time=n+1) to a thresholdvalue. If the bone structure measurement is greater than the thresholdvalue then a decision is made by the algorithm to suggest further futurex-rays. If the bone structure measurement is less than or equal to thethreshold level(s) then the algorithm continues with the next level ofthe decision tree.

[0232] The next level of the decision tree may be an evaluation of thesubject's age and/or gender at time (n) that x-ray is taken, which iscompared to a threshold bone measurement for “normal” subjects of thatage and/or gender. For example, if the subject's bone measurement isgreater than the threshold bone structure level for that particular ageand/or gender, then a decision is made by the algorithm to promptfurther monitoring in the future. If the information on bone structureis less than or equal to the threshold, then the algorithm continueswith the next level of the decision tree.

[0233] The next level of the decision tree may be, for example, anevaluation of the subject's soft tissue (e.g., gum) thickness (n), whichis compared to a threshold measurement. For example, if the soft tissueis significantly below or above the normal range of thickness, then adecision is made by the algorithm to examine more of the x-ray image orto predict a bone-related problem.

[0234] The decision tree could be further elaborated by adding furtherlevels. For example, after a determination that a bone and/orperiodontal events are possible, the subject can be x-rayed again to seeif values have changed. Again, age, gender, weight, soft tissuethickness and the like can also be tested and considered to confirm theprediction.

[0235] In such decision trees, the most important attribute is typicallyplaced at the root of the decision tree. In one embodiment of thepresent invention the root attribute is the current bone structuremeasurement(s). In another embodiment, a predicted bone structuremeasurement at a future time point may be the root attribute.Alternatively, bone mineral density and/or implant structure could beused as the root attribute.

[0236] Further, thresholds need not (but can) be established a priori.The algorithm can learn from a database record of an individualsubject's readings and measurements. The algorithm can train itself toestablish threshold values based on the data in the database recordusing, for example, a decision tree algorithm.

[0237] Further, a decision tree may be more complicated than the simplescenario described above. For example, if soft tissue of a particularsubject is very thick, the algorithm may set a threshold for the bonemeasurements that is higher or lower than normal.

[0238] By selecting parameters (e.g., current or future boneinformation, etc.) and allowing the algorithm to train itself based on adatabase record of these parameters for an individual subject, thealgorithm can evaluate each parameter as independent or combinedpredictors of disease and/or implant failure. Thus, the prediction modelis being trained and the algorithm determines what parameters are themost important indicators. A decision tree may be learnt in an automatedway from data using an algorithm such as a recursive partitioningalgorithm. The recursive partitioning algorithm grows a tree by startingwith all the training examples in the root node. The root node may be“split,” for example, using a three-step process as follows. (1) Theroot node may be split on all the attributes available, at all thethresholds available (e.g., in a training database). To each consideredsplit a criteria is applied (such as, GINI index, entropy of the data,or message length of the data). (2) An attribute (A) and a threshold (T)are selected which optimize the criteria. This results in a decisiontree with one split node and two leaves. (3) Each example in thetraining database is associated with one of these two leaves (based onthe measurements of the training example). Each leaf node is thenrecursively split using the three-step process. Splitting is continueduntil a stopping criteria is applied. An example of a stopping criteriais if a node has less than 50 examples from the training database thatare associated with it.

[0239] In a further embodiment, at each level of the decision in thedecision tree, the algorithm software can associate a probability withthe decision. The probabilities at each level of decision can beevaluated (e.g., summed) and the cumulative probability can be used todetermine whether disease and/or implant failure is predicted. ReceiverOperating Characteristic (ROC) curve analysis can be applied to decisiontree analysis described above. ROC analysis is another thresholdoptimization means. It provides a way to determine the optimal truepositive fraction, while minimizing the false positive fraction. A ROCanalysis can be used to compare two classification schemes, anddetermine which scheme is a better overall predictor of the selectedevent (e.g., evidence of osteoporosis); for example, a ROC analysis canbe used to compare a simple threshold classifier with a decision tree.ROC software packages typically include procedures for the following:correlated, continuously distributed as well as inherently categoricalrating scale data; statistical comparison between two binormal ROCcurves; maximum likelihood estimation of binormal ROC curves from set ofcontinuous as well as categorical data; and analysis of statisticalpower for comparison of ROC curves. Commercial software for structuringand execution of ROC is available (e.g., Analyse-It for Microsoft Excel,Analyse-It Software, Ltd., Leeds LS12 5XA, England, UK; MedCalc®,MedCalc Software, Mariakerke, Belgium; AccuROC, Accumetric Corporation,Montreal, Quebec, Canada).

[0240] Related techniques that can be applied to the above analysesinclude, but are not limited to, Decision Graphs, Decision Rules (alsocalled Rules Induction), Discriminant Analysis (including StepwiseDiscriminant Analysis), Logistic Regression, Nearest NeighborClassification, Neural Networks, and Naive Bayes Classifier.

[0241] All of these aspects of the invention can be practiced separatelyor in combination. Typically, the use of combinations of the embodimentslisted above is more advantageous. Further, although preferredembodiments of the subject invention have been described in some detail,it is understood that obvious variations can be made without departingfrom the spirit and the scope of the invention.

EXPERIMENTAL

[0242] Below are examples of specific embodiments for carrying out thepresent invention. The examples are offered for illustrative purposesonly, and are not intended to limit the scope of the present inventionin any way.

EXAMPLE 1 In vivo Reproducibility and in vivo Diagnostic Sensitivity

[0243] A. Dental X-Rays

[0244] In order to test in vivo reproducibility of data obtained fromdental x-rays, the following experiment was performed. Subjects sat in adental chair and an x-ray was taken of the area of the incisor teeth andof the molar teeth of the mandible. A calibration phantom step wedge wasattached to the dental x-ray film. The dental x-ray film was exposedusing standard x-ray imaging techniques for x-rays of the incisor area.The subjects walked around for 15 minutes at which point that test wasrepeated using the same procedure.

[0245] X-ray films were digitized on a commercial flat-bed scanner withtransparency option (Acer ScanPremio ST). The regions of interest (ROIs)were placed manually at the same position with respect to the dentalroots in all digitized x-rays of the same subject using the NIH Imagesoftware program (http://rsb.info.nih.gov/nih-image/Default.html). Thereproducibility of the measurement of the average gray values inside theROIs was determined as the coefficient of variation (COV=standarddeviation of measurements/mean of measurements). Overall results aregiven as root mean square$( {{RMS} = \sqrt{\sum\limits_{1}^{n}{x_{i}^{2}/n}}} )$

[0246] over both subjects. The data are summarized in Table 2. TABLE 2Reproducibility of measurements of average gray values in digitizeddental x-rays Region COV Subject A COV Subject B RMS Incisor 2.9% (n =3) 5.9% (n = 3) 4.6% Molar 3.0% (n = 3) 4.1% (n = 4) 3.6% All regions:4.2%

[0247] The data show that reproducibility is achieved that is alreadycomparable with that of many ultrasound systems to diagnoseosteoporosis.

[0248] B. Hip Radiographs

[0249] To test whether bone texture analysis in hip x-rays can detectdifferences between normal and osteoporotic bone, sample hip x-rayimages were acquired in two patients with a Fuji FCR 5000 computedradiography system (Fuji Medical Systems, Stemford, Conn.). The firstpatient had normal bone mineral density in the hip as measured by DXA.In the second patient, femoral neck BMD measured by DXA was one standarddeviation below normal.

[0250] For x-ray imaging, patients were positioned on the x-ray table insupine position, parallel to the long axis of the table. The patient'sarms were placed alongside their body. Patient comfort was ensured witha pillow underneath the patient's neck. However, no pillows were usedunderneath the knees. The x-ray technologist checked that the patientlies straight on the table by looking from the head down towards thefeet (which were placed in neutral position with the toes pointing up.The ray was centered onto the hip joint medial and superior to thegreater trochanter.

[0251] Anteroposterior hip radiographs were acquired using the followingparameters: Film-focus distance: 100 cm; tube voltage: 65 kVp; exposure:phototimer for automatic exposure or approximately 20 mAs for manualexposure; collimation: limited to the hip joint, including proximalfemoral diaphysis; centering: over femoral head (see above); tubeangulation: zero degrees. An aluminum step wedge (BioQuest, Tempe,Ariz.) was included in the images to calibrate gray values beforefurther image analysis. Processing was performed using ImageJ, a Javaversion of NIH image (http://rsb.info.nih.gov/ij/).

[0252] Six regions of interest were selected manually at the approximatelocations as shown in FIG. 9. Trabeculae were extracted throughbackground subtraction. The resulting binarized images are shown in theFigures. In a next step, the trabecular bone in the selected regions ofinterest was skeletonized.

[0253] The binarized ROI's in the normal and the osteopenic patient wereused to determine the trabecular density ratio (trabecular area vs. ROIarea). The following bone structure measurements were obtained from theskeletonized ROI's; mean segment length, total skeleton length(normalized by ROI area), skeleton segment count (normalized by ROIarea), and skeleton node count (normalized by ROI area). Results areshown in Tables 3 through 7. TABLE 3 Trabecular Density Ratio(Trabecular Area /ROI Area) ROI A ROI B ROI C ROI D ROI E ROI F Normal0.473 0.482 0.514 0.494 0.476 0.485 Osteopenia 0.382 0.455 0.492 0.4260.424 0.455 % Osteopenia 81%   94%   96%   86%   89%   94%   vs. Normal

[0254] TABLE 4 Mean skeleton segment length ROI A ROI B ROI C ROI D ROIE ROI F Normal  7.116  8.071 10.765  8.175  8.272  7.313 Osteopenia 7.146  9.877 10.004  6.699  8.607  9.750 % Osteopenia 100% 122% 93% 82%104% 133% vs. Normal

[0255] TABLE 5 Total Skeleton Length (normalized by ROI area) ROI A ROIB ROI C ROI D ROI E ROI F Normal  0.0736  0.0758  0.0906  0.0889  0.0806 0.0785 Osteopenia  0.0503  0.0589  0.0672  0.0584  0.0681  0.0543 %Osteopenia 68% 78% 74% 66% 84% 69% vs. Normal

[0256] TABLE 6 Skeleton segment count (normalized by ROI area) ROI A ROIB ROI C ROI D ROI E ROI F Normal  0.0100  0.0094  0.0084  0.0109  0.0097 0.0107 Osteopenia  0.0070  0.0060  0.0067  0.0087  0.0079  0.0056 %Osteopenia 68% 63% 80% 80% 81% 52% vs. Normal

[0257] TABLE 7 Skeleton node count (normalized by ROI area) ROI A ROI BROI C ROI D ROI E ROI F Normal  0.0198  0.0210  0.0229  0.0244  0.0156 0.0240 Osteopenia  0.0090  0.0117  0.0132  0.0113  0.0088  0.0081 %Osteopenia 46% 56% 58% 47% 56% 34% vs. Normal

[0258] These results demonstrate that the evaluation of trabecularstructure reveals significant differences between normal and osteopenicbone and that selective analysis of trabeculae oriented in certaindirections in the different ROI allows for the assessment of structurescritical for biomechanical stability of the proximal femur.

EXAMPLE 2 Image Processing Techniques

[0259] Techniques to analyze structure of trabeculae in differentregions of the femoral head, neck, and proximal shaft are developed inMatlab (The MathWorks, Inc., Natick, Mass.) on PC's. The followingtechiques (modules) are developed: algorithms for software analysis ofdensity, length, thickness, and orientation of trabeculae in differentregions of interest (ROI) in the radiograph and a technique forautomated placement of these ROI.

[0260] Six regions of interest are selected in the proximal femur forbone microstructure evaluation. The size and shape of these ROI aredesigned to capture the local changes of trabecular density andstructure (see, e.g., FIG. 9), and may reflect the location of thedifferent compressive and tensile groups of trabeculae. Singh et al.(1970) J Bone Joint Surg Am. 1970. 52:457-467. Thus, a classificationscheme based on statistical convergence of multiple parameters thatwould provide a high precision index for predicting hip fractures isdeveloped.

EXAMPLE 3 Bone Structure Analysis of Hip Radiographs

[0261] The trabeculae in the femur is extracted using the backgroundsubtraction method, essentially as described in Geraets et al. (1998)Bone 22:165-173. A copy of the image is blurred with a 15×15 Gaussianfilter, and the result represents the non-uniform background. Thisbackground image is subtracted from the original image to obtain animage of trabecular structure. This image is then transformed intobinary image of trabecular structure by applying a threshold value of 0.An example of the end result is shown in FIG. 10.

[0262] In a second step, parameters relevant to the geometry andconnectivity of trabecular structure are measured on the trabecularskeleton or centerline. The skeletonization is performed usingmorphological hit-or-miss thinning for example as described in Soille,“Morphological image analysis: principles and application” Springer,1998: p. 129-154. The branch points and end points of the skeletonnetwork are detected, and the skeleton segments are classified asfree-end segments and node-to-node segments.

[0263] One or more of the following parameters from the binarized andfrom the skeletonized ROI's are used: trabecular density; ratio oftrabecular area to total ROI area; trabecular perimeter; star volume(Ikuta et al. (2000) J Bone Miner Res. 18:271-277; Vesterby (1990) Bone11:149-155); trabecular bone pattern factor (Hahn et al. (1992) Bone13:327-330); Euclidean distance transform; assessment of trabecularorientation using Fourier analysis; and orientation-specific trabecularassessment. Further, one or more of the following parameters can bemeasured in each ROI on the network of skeletonized trabeculae as awhole, all skeleton segments, and each type of segment: segment count;segment length; angle of segment orientation; and InterconnectivityIndex (Legrand et al. (2000) J. Bone Miner Res. 15:13-19): normalizedratio of the number of node-to-node segments to free-end segments.

[0264] For example, in Euclidean Distance Transform each pixel on thebinarized trabeculae is assigned a value equal to its Euclidean distancefrom the structure boundary. Thus, thicker trabeculae will have largerdistance transform values in the center, thereby estimating trabecularthickness calculates the mean of the distance transform values along thetrabecular skeleton (see FIG. 11). Further, multiplying this value by 2provides a measurement of trabecular thickness.

[0265] Similarly, predominant trabeculae orientation may be evaluatedusing the 2D Fast Fourier Transform (FFT). A rectangular region isselected within each ROI and multiplied with a 2D Kaiser window beforeapplying the transform (see FIG. 12, left). The log of the Fouriermagnitude is taken to form an image representing the frequency domain ofthe ROI. The result is then filtered with a 5×5 Gaussian filter toreduce local variation. An example image is shown in FIG. 12, center.The Fourier image is subsequently thresholded at a fixed magnitudelevel. This binary image is resampled to a square image to normalize thelength of the vertical and horizontal axes, and the direction and lengthof its major axis are determined (FIG. 12, right). The angles will bemeasured with respect to the axes of the femoral neck and shaft. Theaxes are determined by fitting lines to the two longest segments of thecenterline of the binarized femur (see also FIG. 14). The ROI's arelocated such that they include the different groups of compressive andtensile trabeculae in the proximal femur that each can be characterizedby a specific direction. A fully automated technique to evaluate thedifferent quantitative structural parameters explained above for thosetrabeculae in each of the ROI that are oriented in the characteristicdirection expected for the particular ROI is developed.

[0266] The orientation of each trabecular skeleton segment is foundthrough the gradient of the line fitted to the skeleton points. Based onthis orientation information, only those trabeculae are considered inthe evaluation of the structure parameters that are approximatelyoriented in the characteristic direction for a particular ROI.

EXAMPLE 4 Multidimensional Classification

[0267] Example 3 describes a number of parameters that are measured toassess trabecular structure in different regions of the proximal femur.In this Example, the different structural parameters are combined ineach section, and a single index is determined over all regions ofinterest.

[0268] A training set of hip x-ray images of a group of subjects aredivided into the two categories “osteoporosis” and “no osteoporosis”,based on previous DXA results. Subsequently, for all x-rays in thetraining set, the parameters listed in Example 3 are calculated for allregions of interest placed as described in Example 3, resulting in a setof m-dimensional prototype feature vectors f_(i)=(f_(i1), . . . ,f_(im))^(T) for the training set I={I_(i)}, i=1, . . . , n.

[0269] For each parameter a single scalar index value is calculated. Allindex values are combined into one n-dimensional feature vector. In onestep, the system is trained with the data from clinical validationstudies with premenopausal, postmenopausal healthy and postmenopausalosteoporotic subjects. The subject groups are preferably divided into a“fracture” and a “no fracture” category. The feature vectors calculatedfrom the x-ray images are used as prototype patterns.

[0270] For each patient, a feature vector is calculated from the x-rayas calculated for the prototype patterns and an individual patientclassified as category C if the majority of the k closest prototypepatterns is of the category C. The distance d between the patient'sfeature vector f=(f₁, f₂, . . . , f_(n))^(T) and a prototype patternp=(p₁, p₂, . . . , p_(n))^(T) is defined by the Euclidean norm L₂:${d( {f,p} )} = {{L_{2}( {f,p} )} = \sqrt{\sum\limits_{i = 1}^{n}( {f_{i} - p_{i}} )^{2}}}$

[0271] The optimum scale for the different parameters is also preferablydetermined. However, for some parameters differences in the index valuesbetween the categories is smaller than for others. Also, the optimum kwill be determined. Increasing k is expected to improve the accuracy ofthe classification, but it has to be smaller than the number ofprototypes in each category. The exact percentage value of the majorityof the k closest prototype patterns that determines the classificationprovides a measure for the reliability of the classification. The higherthe percentage of prototype patterns from a particular category C, themore significant the information provided by the classification islikely to be.

[0272] This classification approach is validated with a series ofleave-one-out experiments using the 0° neutral position images of thefemoral position study (see Example 8) and the baseline hip x-rays ofthe short-term in vivo reproducibility study. For these experiments,each subject is preferably used as a test case once. The training setfor the system consists of the patterns calculated for all or most ofthe remaining subjects. The test case is correctly classified using thistraining set, and the diagnostic sensitivity and specificity of thecombination of bone structure parameters is determined.

[0273] In addition to the measurements described above (which provideindex values for the parameters “length of trabeculae”, “direction oftrabeculae and anisotropy”, and “trabecular thickness”), additionalmeasurements for other parameters in the classification system that havebeen explored in the past to study bone density and structure fromx-ray, CT, and MR images such as: (1) mean pixel intensity; (2) varianceof pixel intensity; (3) Fourier spectral analysis; (4) fractaldimension; (5) morphological parameters such as the trabecular area,trabecular periphery, total trabecular length, number of terminal andbranch points, as well as similar parameters for the bone marrow can beused.

EXAMPLE 5 Automated Placement of Region of Interest (ROI)

[0274] Analysis of x-rays (e.g., hip radiographs) may be facilitated bydevelopment of techniques that locate one or more regions of interest(ROI) used for the calculation of the structural parameters of thetrabecular bone. For example, the general position of the femur can belocated using a binary image of the hip radiographs thresholded at theappropriate gray value. In a typical hip radiograph, the femur is abright structure extending from the pelvis. (FIG. 13). By thresholdingthe digitized radiograph at the typical femur intensity value, a binaryimage showing the femur is produced. The relatively thin structure ofthe femoral shaft can be extracted by applying a morphology operation onthe binary image. The morphological top-hat filter (opening subtractedfrom input) with an upright rectangular structuring element segments thefemoral shaft. The result is shown in FIG. 13 with outline of thebinarized femur superimposed on the original radiograph. The region iscropped for further processing, preferably leaving enough room toinclude the femoral head.

[0275] To position the set of predetermined ROI, a regularized activeshape algorithm can be used (Behiels et al. (1999) Proceedings of the2nd International Conference on Medical Image Computing andComputer-Assisted Intervention—MICCAI'99, Lecture notes in ComputerScience 1679:128-137; Cootes (1994) Image and Vision Computing12:355-366). A general model of the proximal femur is created bymanually outlining the shape in a training set of typical hipradiographs to form a mean shape. The six predefined ROI are thenembedded into this model. This mean model is scaled down 80%,isometrically along its centerline. This transformation is applied tothe predefined ROI as well. The outline of the rescaled model is thenused as the initial template and is positioned within the proximal femurin the input image. The control points of the contour are subsequentlyexpanded outwards away from the nearest centerline point. The energyfunction to be optimized in this iterative process can take into accountlocal features, such as gradient, intensity, deviation from the meanmodel, and curvature of contour segments. FIG. 14 illustrates thepropagation of the initial control points towards the femur edge. Whenthe iteration is completed, a deformation field for the model area iscalculated. This deformation field is interpolated for the model ROIinside the boundaries of the femur model. The result is a new set of ROIthat is adapted to the input image, but similar to the model ROI withrespect to anatomical landmarks (see FIG. 9).

EXAMPLE 6 Data Analysis

[0276] Patients are selected into one of three groups: healthypremenopausal (PRE); healthy postmenopausal (POST), and osteoporoticpostmenopausal (OSTEO) women. All groups are studied by: (1) dentalx-ray images of the periapical and canine region; (2) quantitativecomputed tomography of the spine and (3) hip; (4) dual x-rayabsorptiometry of the spine and (5) hip; (6) single x-ray absorptiometryof the calcaneus, and (7) ultrasound of the calcaneus using standardtechniques. A diagnosis of osteoporosis is made when at least oneatraumatic vertebral fracture as determined by a semi-quantitativeassessment of morphologic changes of the thoracic and lumbar spine onlateral conventional x-rays is observed.

[0277] The means and standard deviations of the different bone structuremeasurements (see above) and bone mineral density measurements(mandibular BMD, QCT spine, QCT hip, DXA spine, DXA hip, SXA calcaneus,ultrasound calcaneus) are calculated for each patient group. TheStudent's t-test (t-values and p-values) and percent decrement are usedfor comparing the different measurements for reflecting intergroupdifferences. Annual, age-related changes are expressed as percentchanges relative to the predicted values at age 30 and as fractionalstandard deviation (SD) of PRE. Correlations with age along withp-values are also be reported. Odds ratios (for ISD change in themeasured parameter) and 95% confidence limits based on the age-adjustedlogistic regression are calculated to measure the discriminative ability(for discriminating between the postmenopausal osteoporotic and thenormal postmenopausal group) and the risk of osteoporotic fractureassociated with the measured parameter. The pairwise comparisons of thediscriminative abilities are tested using age-adjusted receiveroperating characteristic (ROC) curve analysis.

[0278] Pairwise comparisons of all techniques are obtained by poolingall subjects (PRE, POST, OSTEO) and using Pearson's correlationcoefficients (r), percent standard errors of the estimate (CV), andp-values for testing significance of correlations.

[0279] To compare measurements for their diagnostic ability, a kappascore analysis is performed on the normal postmenopausal women (POST)and the osteoporotic postmenopausal women (OSTEO). This is done byclassifying every woman from the postmenopausal groups as osteopenic ifher T-score with respect to the reference group (PRE) is less (or incase of structural parameters also greater) than 2.5. The T-score for anindividual woman and a particular measurement is defined as themeasurement minus the mean measurement of young normals (PRE) divided bythe SD of the measurement in the PRE group. Note that the T-score ismeasuring the position of an individual woman with respect to the PREgroup and is different from the Student's t-value.

EXAMPLE 7 Longitudinal Monitoring of Bone Structure

[0280] Algorithms and software to match follow-up dental x-rays obtainedat a time point T₂ relative to baseline x-rays of the mandible obtainedat an earlier time point T₁ are developed. For purposes of monitoring oftherapeutic response, bone structure parameters have to be measured atthe same location of the mandible at different points in time. Thus, inorder to compensate for differences in patient positioning and in orderto find corresponding regions of interest (ROI's) for comparison of theresults between baseline and follow-up examinations, it is desirable toregister two dental x-ray images.

[0281] Due to possible slight differences in the projection angle of thex-ray beam on the film in the two images to be registered, an elasticmatching step is preferably included. The first step, however, is aglobal affine transformation, for which the mutual information is usedas a cost function. Wells et al. (1996) Medical Image Analysis 1:35-51.The mutual information I_(M,N) of two images M and N is defined as$I_{M,N} = {\sum\limits_{({m,n})}{{p_{MN}( {m,n} )}\quad {{\log ( \frac{p_{MN}( {m,n} )}{{p_{M}(m)}{p_{N}(n)}} )}.}}}$

[0282] Here, the gray values occurring in the two images are regarded asrandom variables, and the mutual information provides a measure of thestrength of the dependence between these variables. p_(M) and p_(N) arethe distributions of M and N respectively, and p_(MN) is the jointdistribution of M and N. Maintz et al. (1998) SPIE Medical Imaging—ImageProcessing. These distributions can be approximated from the marginaland joint gray value histograms, more accurately with the use of aParzen window function. Powell's method can be used as an optimizationscheme to find the best affine transformation for N to match it with M.Press et al. (“Numerical Recipes in C.” 2nd edition, 1992, CambridgeUniversity Press.

[0283] This global transformation is followed by local elasticadjustments to improve the match. To achieve this, the conditionalprobability densities p(n|m) are estimated from the joint histogram ofthe globally registered images. The transformation vector field t(x) isthen determined such that N(x-t(x)) is as similar to M(x) as possible bymaximizing the local gray value correspondence, which for a fixed valueof x is defined as

c _(x)(t)=∫w(x′−x)p(N(x′−t)|M(x′))dx′.

[0284] Here, w is a window function whose width determines the size ofthe region that is used to compute t(x). To determine the windowfunction, an approach similar to the one described in Warfield et al.“Brain Warping” 1999, Academic Press, p:67-84 is used. A number ofsuccessively wider window functions w, are combined into a single window${w = {\sum\limits_{i}{W_{i}w_{i}}}},$

[0285] where the weights W₁ are given as$W_{i} = {\frac{1}{\sum\limits_{i}{\det ( Q_{i} )}}{\det ( Q_{i} )}}$with  Q_(i) = ∫w_(i)(x^(′) − x)∇N(x^(′))∇N^(T)(x^(′))x^(′).

[0286] The exact location of the ROI after automatic placement in thebaseline image for a particular patient is kept in a database. When thepatient returns for a follow-up exam, the new image is registered withthe baseline image, and thus transformed into the coordinate system ofthe baseline image. The bone structure in the registered follow-up x-raycan then be measured at exactly the same position as in the baselineimage.

EXAMPLE 8 Influence of Positioning of the Femur on Bone StructuralMeasurements

[0287] The effect(s) of the positioning of the femur on each parameterof the bone structure assessments is (are) examined. Hip x-rays areobtained in normal postmenopausal women and postmenopausal women withosteoporosis in neutral position and in various degrees of internal andexternal rotation.

[0288] The diagnosis of osteoporosis is made when at least oneatraumatic vertebral fracture as determined by a semi-quantitativeassessment of morphologic changes of the thoracic and lumbar spine onlateral conventional radiographs is observed. See, also, Genant et al.(1993) J. Bone Miner Res. 8:1137-1148.

[0289] Standard anteroposterior hip radiographs are obtained with theextremity at 30° internal rotation, 15° internal rotation, 0°, 15°external rotation, and 30° external rotation. These angles are achievedby placing the foot and ankle against a 30° or a 15° degree wedge ineither internal or external rotation of the femur. The foot is securedagainst the wedge using Velcro straps.

[0290] The effect of positioning is assessed by calculating the pairwise coefficient of variation (CV %) between the results for the 0°position and the other positions for each individual subjects. Theangular dependency will be expressed for each of the angles 30° internalrotation, 15° internal rotation, 15° external rotation, and 30° externalrotation as the root-mean-square of these CV % values over all subjects.In general, parameters with the least dependency on angular positioningof the femur are selected.

[0291] If the pair wise coefficient of variation between the results forthe 0° neutral position and the 15° internal or external rotationposition exceed 10% for the majority of the structural parametersmeasured, a foot holder that fixes the patients' foot in neutralposition can be used The foot holder is designed with a base plateextending from the mid to distal thigh to the heel. The base platepreferably sits on the x-ray table. The patients' foot is positioned sothat the posterior aspect of the heel is located on top of the baseplate. The medial aspect of the foot is placed against a medial guideconnected rigidly to the base plate at a 90° angle. A second, lateralguide attached to the base plate at a 90° angle with a sliding mechanismwill then be moved toward the lateral aspect of the foot and will belocked in position as soon as it touches the lateral aspect of the foot.The foot will be secured to the medial and lateral guide using Velcrostraps. It is expected that the degree of involuntary internal orexternal rotation can be limited to less than 5° using this approach.

EXAMPLE 9 Influence of X-Ray Tube Angulation on Bone StructuralMeasurements

[0292] The effect(s) of the positioning of the x-ray tube on eachparameter of the bone structure assessments is (are) examined. Dentalx-rays are obtained in normal postmenopausal women and postmenopausalwomen with osteoporosis. The diagnosis of osteoporosis is made when atleast one atraumatic vertebral fracture as determined by asemi-quantitative assessment of morphologic changes of the thoracic andlumbar spine on lateral conventional radiographs is observed. See, also,Genant et al. (1993) J. Bone Miner Res. 8:1137-1148.

[0293] Standard anteroposterior dental radiographs are obtained in theincisor region of the mandible. The x-ray tube is aligned with an angleof 0°, 10°, 20°, 30°, and −10°, −20°, and −30° relative to the dentalx-ray film. These angles are achieved with use of a goniometer appliedto the metal tube located in front of the dental x-ray tube. The dentalx-ray film is positioned at the posterior mandibular wall in the incisorregion.

[0294] The effect of positioning is assessed by calculating the pairwise coefficient of variation (CV %) between the results for the 0°position and the other tube positions for each individual subject. Theangular dependency will be expressed for each of the angles as theroot-mean-square of these CV % values over all subjects.

[0295] The results indicate that a 10 degree tube angulation can resultin a 12% error in apparent density.

[0296] A mechanical alignment system is then applied to the Rinn holder.For this purpose, an extension tubing is attached to the Rinn holder.The extension tubing is designed so that its inner diameter is slightlygreater (and fits over) than the outer diameter of the dental x-raysystem metal tube (FIG. 15). The dental x-ray system metal tube is theninserted into the extension tubing attached to the Rinn holder whichreduces alignment error of the x-ray tube relative to the x-ray film.One group of patients then undergo two x-rays each of the incisorregion. The results indicate that the short-term in-vivo reproducibilityerror of dental bone density and bone structure measurements is reducedwith use of the mechanical alignment system by reducing x-ray tubeangulation relative to the dental film and the anatomic landmarks in themandible.

EXAMPLE 10 Measurement of Bone Structure and Selecting Therapy

[0297] An x-ray image of a mandible or a hip or spine or other bone isanalyzed using a computer program capable of assessing bone structure,for example as described above. The computer program derives ameasurement of one or more structural parameters of the trabecular bone.The measurement of the structural parameter(s) is compared against adatabase containing information on said one or more structuralparameters in normal, healthy age-, sex-, and race matched controls. Ifthe patient's measurement of bone structure differs by more than 2standard deviations from the age-, sex-, and race matched mean ofnormal, healthy subjects, a report is sent to the physician who thenselects a therapy based on the measurement of bone structure.

EXAMPLE 11 Measurement of Bone Structure and Monitoring Therapy

[0298] One or more x-ray images (mandible, hip or spine or other bone)are obtained from a patient undergoing therapy for osteoporosis, forexample using an anabolic or an antiresorptive drug at two differenttime points T1 and T2. The x-rays are analyzed using a computer programcapable of assessing bone structure. The computer program derives ameasurement of one or more structural parameters of the trabecular bonefor both time points T1 and T2. The measurement of the structuralparameter(s) at T1 and T2 is compared against a database containinginformation on said one or more structural parameters in normal, healthyage-, sex-, and race matched controls for each time point. If theresults indicate that the patient has lost 5% or more bone between timepoints T1 and T2 despite therapy, a physician selects a different, moreaggressive therapy.

What is claimed is:
 1. A method to derive information on bone structurefrom an image comprising: (a) obtaining an image from a subject; (b)analyzing the image obtained in step (a) to derive quantitativeinformation on bone structure; and (c) comparing the information on bonestructure obtained from the image to a database of bone structuremeasurements obtained from selected subjects.
 2. The method of claim 1,wherein the image is an x-ray image.
 3. The method of claim 1, whereinthe image is an electronic image.
 4. The method of claim 1, wherein theimage comprises an external standard.
 5. The method of claim 1, whereinthe selected subjects are normal subjects.
 6. The method of claim 1,wherein the selected subjects are osteoporosis subjects.
 7. The methodof claim 1, wherein said database comprises demographic data and data onbone structure in the subjects.
 8. The method of claim 1, wherein saidsubjects are age, sex and race-matched to said subject.
 9. The method ofclaim 1, wherein the bone structure information is selected from thegroup consisting of trabecular thickness; trabecular spacing; trabecularconnectivity, two-dimensional or three-dimensional spaces betweentrabecular; two-dimensional or three-dimensional architecture of thetrabecular network.
 10. The method of claim 2, further comprising thestep of locating one or more regions of interest (ROI) in said x-rayimage.
 11. The method of claim 8, wherein said ROI is positioned using aregularized active shape alogrithm.
 12. The method of claim 10, whereinthe ROI are located automatically.
 13. The method of claim 1, whereinstep (b) comprises analyzing the image obtained in step (a) using one ormore indices selected from the group consisting of trabecular density,trabecular perimeter, star volume, trabecular bone pattern factor,trabecular thickness, trabecular orientation, orientation-specifictrabecular assessment, trabecular connectivity and combinations thereof,thereby deriving quantitative information on bone structure.
 14. Themethod of claim 13, wherein at least one of the indices trabeculardensity and wherein said density is a ratio of trabecular area to totalarea.
 15. The method of claim 13, wherein at least one of the indices isorientation-specific trabecular assessment as determined using Fourieranalysis.
 16. The method of claim 13, wherein at least one of theindices is trabecular thickness as determined by Euclidean distancetransformation.
 17. The method of claim 13, wherein at least one of theindices is trabecular orientation as determined using 2D fast FourierTransform (FFT).
 18. The method of claim 13, wherein at least one of theindices is trabecular connectivity as determined using node count. 19.The method of claim 13, wherein two or more indices are analyzed.
 20. Amethod of diagnosing a bone condition in a subject comprising analyzinginformation from an image according to the method of claim 1, wherein ifsaid analysis indicates that the bone structure information obtainedfrom the subject differs from that of normal control subjects, a bonecondition is diagnosed.
 21. The method of claim 20, wherein the bonecondition is osteoporosis.
 22. A method of treating a bone conditioncomprising (a) obtaining an image from a subject; (b) analyzing theimage obtained in step (a) to derive quantitative information on bonestructure; (c) diagnosing a bone condition based on the analysis of step(b); and (d) selecting and administering a suitable treatment to saidsubject based on said diagnosis.
 23. The method of claim 22, furthercomprising the step of comparing the information with information in adatabase of bone structure measurements obtained from selected subjects.24. The method of claim 22, wherein the treatment comprisesadministering one or more antiresorptive agents.
 25. The method of claim22, wherein the treatment comprises administering one or more anabolicagents.
 26. The method of claim 24, wherein the treatment furthercomprises administering one or more anabolic agents.
 27. A method ofdetermining bone mineral density from an x-ray image, the methodcomprising the steps of (a) determining density of one or more internalstandards in said image; (b) creating a weighted mean between the valuesobtained in step (a); (c) utilizing said weighted mean to determine bonemineral density of bone in said image.
 28. The method of claim 27,wherein the internal references are selected from the group consistingof air, fat, water, metal and combinations thereof.
 29. A method ofdetermining bone structure from an x-ray image comprising the steps of(a) identifying one or more internal standards on said x-ray image; (b)determining the density or structure of said standard; and (c) utilizingthe density, structure or combinations thereof of said standard todetermine bone structure of the x-ray image.
 30. The method of claim 29,wherein said internal standard is selected from the group consisting ofa tooth, a portion of a tooth, cortical bone, air, subcutaneous fat, andmuscle.
 31. A method of evaluating bone disease in a subject, the methodcomprising the steps of: (a) obtaining an x-ray image from said subject,wherein said image includes one or more bones; (b) assessing bonemineral density in at least one anatomic region of said image; (c)assessing bone structure in said region; and (d) combining saidassessments of bone mineral density and bone structure to evaluate bonedisease.
 32. The method of claim 31, wherein said bone disease comprisesthe risk of bone fracture or the risk of osteoporotic fracture.
 33. Themethod of claim 31, wherein said evaluation comprises diagnosing bonedisease.
 34. The method of claim 31, wherein said evaluation comprisesmonitoring the progression of bone disease.
 35. The method of claim 31,further comprising selecting a therapy based on the evaluation of bonedisease and administering said therapy to said subject.
 36. The methodof claim 35, wherein said evaluation comprises monitoring theprogression of bone disease during or after administration of saidselected therapy.
 37. The method of claim 31, further comprising thestep of assessing one or more macro-anatomical parameters in said imageand combining said assessment of bone mineral density, bone structureand macro-anatomical parameters to diagnose bone disease.
 38. A methodof treating bone disease in a subject, the method comprising the stepsof: (a) obtaining an image from said subject, wherein said imageincludes one or more bones; (b) assessing bone mineral density in atleast one anatomic region of said image; (c) assessing bone structure insaid region; (d) combining said assessments of bone mineral density andbone structure to evaluate bone disease; (e) selecting a therapy basedon the evaluation of bone disease; and (f) administering said therapy tosaid subject.
 39. The method of claim 38, wherein steps (a) to (d) arerepeated.
 40. The method of claim 38, wherein steps (a) to (e) arerepeated.
 41. A method for evaluating bone disease in a subject, themethod comprising the steps of: (a) obtaining an image of said subjectwherein said image includes one or more bones; (b) assessing bonestructure of said bone in said image; (c) assessing one or moremacro-anatomical parameters in said image; and (d) combining theassessments bone structure and macro-anatomical parameter assessment toevaluate bone disease.
 42. The method of claim 41, wherein said bonedisease comprises the risk of bone fracture.
 43. The method of claim 42,wherein said fracture is osteoporotic fracture.
 44. The method of claim41, wherein said evaluation comprises diagnosing bone disease.
 45. Themethod of claim 41, wherein said evaluation comprises monitoring theprogression of bone disease.
 46. The method of claim 45, wherein themonitoring comprises comprises repeating steps (a) to (d) at two or moretime points.
 47. The method of claim 41, further comprising selecting atherapy based on the evaluation of bone disease and administering saidtherapy to said subject.
 48. The method of claim 47, wherein saidevaluation comprises monitoring the progression of bone disease duringor after administration of said selected therapy.
 49. A method to assessthe presence or severity of a bone disease from an image comprising: (a)obtaining an image from a subject; (b) analyzing the image obtained instep (a) to derive quantitative information on bone structure; and (c)comparing the information on bone structure obtained from the image to adatabase of bone structure measurements obtained from selected subjects,thereby assessing the presence or severity of a disease.
 50. The methodof claim 49, wherein the bone disease is osteoporosis or fracture risk.51. The method of claim 49, wherein the image is an x-ray image.
 52. Themethod of claim 49, wherein the image is an electronic image.
 53. Themethod of claim 49, wherein the image comprises an external standard.54. The method of claim 49, wherein the selected subjects are normalsubjects.
 55. The method of claim 49, wherein the selected subjects areosteoporosis subjects.
 56. The method of claim 49, wherein said databasecomprises demographic data and data on bone structure in the subjects.57. The method of claim 49, wherein said subjects are age, sex andrace-matched to said subject.
 58. The method of claim 49, wherein thebone structure information is selected from the group consisting oftrabecular thickness; trabecular spacing; trabecular connectivity,two-dimensional or three-dimensional spaces between trabecular;two-dimensional or three-dimensional architecture of the trabecularnetwork.
 59. The method of claim 51, further comprising the step oflocating one or more regions of interest (ROI) in said x-ray image. 60.The method of claim 57, wherein said ROI is positioned using aregularized active shape alogrithm.
 61. The method of claim 59, whereinthe ROI are located automatically.
 62. The method of claim 49, whereinstep (b) comprises analyzing the image obtained in step (a) using one ormore indices selected from the group consisting of trabecular density,trabecular perimeter, star volume, trabecular bone pattern factor,trabecular thickness, trabecular orientation, orientation-specifictrabecular assessment, trabecular connectivity and combinations thereof,thereby deriving quantitative information on bone structure.
 63. Themethod of claim 62, wherein at least one of the indices trabeculardensity and wherein said density is a ratio of trabecular area to totalarea.
 64. The method of claim 62, wherein at least one of the indices isorientation-specific trabecular assessment as determined using Fourieranalysis.
 65. The method of claim 62, wherein at least one of theindices is trabecular thickness as determined by Euclidean distancetransformation.
 66. The method of claim 62, wherein at least one of theindices is trabecular orientation as determined using 2D fast FourierTransform (FFT).
 67. The method of claim 62, wherein at least one of theindices is trabecular connectivity as determined using node count. 68.The method of claim 62, wherein two or more indices are analyzed. 69.The method of claim 1, wherein a positioning device is applied to a bodypart or an extremity of the subject prior to obtaining the x-ray image.70. The method of claim 1, wherein said positioning device comprises afoot holder.
 71. The method of claim 1, further comprising the steps ofobtaining an image that does not include a body part of the subject butwhich includes a first calibration phantom; and calibrating the apparentdensity of the first calibration phantom with the apparent density of asecond calibration phantom.
 72. The method of claim 71, wherein an imageobtained from a subject includes said second calibration phantom. 73.The method of claim 71, wherein said first calibration phantom is usedfor comparing different sites.
 74. A method for minimizing tubeangulation of an x-ray tube that includes an x-ray film holder,comprising the steps of providing an attachment mechanism; and attachingthe x-ray system to the x-ray film holder such that tube angulation isminimized.
 75. The method of claim 74, wherein said x-ray film bolderincludes a Rinn instrument.
 76. The method of claim 74, wherein saidattachment mechanism is mechanical.
 77. The method of claim 74, whereinsaid attachment mechanism is electromagnetic.
 78. The method of claim74, wherein said attachment mechanism uses Velcro or and adhesive.
 79. Amethod for minimizing tube angulation of an x-ray tube that includes adental x-ray film holder, comprising the steps of providing an x-raytube alignment system; and aligning the x-ray system substantiallyperpendicular to the x-ray film such that tube angulation is minimized,wherein said alignment system uses optical aids.
 80. The method of claim79, wherein said optical aid comprises one or more levels.
 81. Themethod of claim 79, wherein said optical aid comprises one or morecross-hairs.
 82. The method of claim 79, wherein said optical aidcomprises one or more points or areas of light.